1,261 391 87MB
English Pages 1421 Year 2020
Table of contents :
Cover
Contents
Preface
A Tribute to James Stewart
About the Authors
Technology in the Ninth Edition
To the Student
Diagnostic Tests
A: Diagnostic Test: Algebra
B: Diagnostic Test: Analytic Geometry
C: Diagnostic Test: Functions
D: Diagnostic Test: Trigonometry
A Preview of Calculus
What Is Calculus?
The Area Problem
The Tangent Problem
A Relationship between the Area and Tangent Problems
Summary
Chapter 1: Functions and Models
1.1 Four Ways to Represent a Function
1.2 Mathematical Models: A Catalog of Essential Functions
1.3 New Functions from Old Functions
1.4 Exponential Functions
1.5 Inverse Functions and Logarithms
1 Review
Principles of Problem Solving
Chapter 2: Limits and Derivatives
2.1 The Tangent and Velocity Problems
2.2 The Limit of a Function
2.3 Calculating Limits Using the Limit Laws
2.4 The Precise Definition of a Limit
2.5 Continuity
2.6 Limits at Infinity; Horizontal Asymptotes
2.7 Derivatives and Rates of Change
2.8 The Derivative as a Function
2 Review
Problems Plus
Chapter 3: Differentiation Rules
3.1 Derivatives of Polynomials and Exponential Functions
3.2 The Product and Quotient Rules
3.3 Derivatives of Trigonometric Functions
3.4 The Chain Rule
3.5 Implicit Differentiation
3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
3.7 Rates of Change in the Natural and Social Sciences
3.8 Exponential Growth and Decay
3.9 Related Rates
3.10 Linear Approximations and Differentials
3.11 Hyperbolic Functions
3 Review
Problems Plus
Chapter 4: Applications of Differentiation
4.1 Maximum and Minimum Values
4.2 The Mean Value Theorem
4.3 What Derivatives Tell Us about the Shape of a Graph
4.4 Indeterminate Forms and l'Hospital's Rule
4.5 Summary of Curve Sketching
4.6 Graphing with Calculus and Technology
4.7 Optimization Problems
4.8 Newton's Method
4.9 Antiderivatives
4 Review
Problems Plus
Chapter 5: Integrals
5.1 The Area and Distance Problems
5.2 The Definite Integral
5.3 The Fundamental Theorem of Calculus
5.4 Indefinite Integrals and the Net Change Theorem
5.5 The Substitution Rule
5 Review
Problems Plus
Chapter 6: Applications of Integration
6.1 Areas between Curves
6.2 Volumes
6.3 Volumes by Cylindrical Shells
6.4 Work
6.5 Average Value of a Function
6 Review
Problems Plus
Chapter 7: Techniques of Integration
7.1 Integration by Parts
7.2 Trigonometric Integrals
7.3 Trigonometric Substitution
7.4 Integration of Rational Functions by Partial Fractions
7.5 Strategy for Integration
7.6 Integration Using Tables and Technology
7.7 Approximate Integration
7.8 Improper Integrals
7 Review
Problems Plus
Chapter 8: Further Applications of Integration
8.1 Arc Length
8.2 Area of a Surface of Revolution
8.3 Applications to Physics and Engineering
8.4 Applications to Economics and Biology
8.5 Probability
8 Review
Problems Plus
Chapter 9: Differential Equations
9.1 Modeling with Differential Equations
9.2 Direction Fields and Euler's Method
9.3 Separable Equations
9.4 Models for Population Growth
9.5 Linear Equations
9.6 PredatorPrey Systems
9 Review
Problems Plus
Chapter 10: Parametric Equations and Polar Coordinates
10.1 Curves Defined by Parametric Equations
10.2 Calculus with Parametric Curves
10.3 Polar Coordinates
10.4 Calculus in Polar Coordinates
10.5 Conic Sections
10.6 Conic Sections in Polar Coordinates
10 Review
Problems Plus
Chapter 11: Sequences, Series, and Power Series
11.1 Sequences
11.2 Series
11.3 The Integral Test and Estimates of Sums
11.4 The Comparison Tests
11.5 Alternating Series and Absolute Convergence
11.6 The Ratio and Root Tests
11.7 Strategy for Testing Series
11.8 Power Series
11.9 Representations of Functions as Power Series
11.10 Taylor and Maclaurin Series
11.11 Applications of Taylor Polynomials
11 Review
Problems Plus
Chapter 12: Vectors and the Geometry of Space
12.1 ThreeDimensional Coordinate Systems
12.2 Vectors
12.3 The Dot Product
12.4 The Cross Product
12.5 Equations of Lines and Planes
12.6 Cylinders and Quadric Surfaces
12 Review
Problems Plus
Chapter 13: Vector Functions
13.1 Vector Functions and Space Curves
13.2 Derivatives and Integrals of Vector Functions
13.3 Arc Length and Curvature
13.4 Motion in Space: Velocity and Acceleration
13 Review
Problems Plus
Chapter 14: Partial Derivatives
14.1 Functions of Several Variables
14.2 Limits and Continuity
14.3 Partial Derivatives
14.4 Tangent Planes and Linear Approximations
14.5 The Chain Rule
14.6 Directional Derivatives and the Gradient Vector
14.7 Maximum and Minimum Values
14.8 Lagrange Multipliers
14 Review
Problems Plus
Chapter 15: Multiple Integrals
15.1 Double Integrals over Rectangles
15.2 Double Integrals over General Regions
15.3 Double Integrals in Polar Coordinates
15.4 Applications of Double Integrals
15.5 Surface Area
15.6 Triple Integrals
15.7 Triple Integrals in Cylindrical Coordinates
15.8 Triple Integrals in Spherical Coordinates
15.9 Change of Variables in Multiple Integrals
15 Review
Problems Plus
Chapter 16: Vector Calculus
16.1 Vector Fields
16.2 Line Integrals
16.3 The Fundamental Theorem for Line Integrals
16.4 Green's Theorem
16.5 Curl and Divergence
16.6 Parametric Surfaces and Their Areas
16.7 Surface Integrals
16.8 Stokes' Theorem
16.9 The Divergence Theorem
16.10 Summary
16 Review
Problems Plus
Appendixes
Appendix A: Numbers, Inequalities, and Absolute Values
Appendix B: Coordinate Geometry and Lines
Appendix C: Graphs of SecondDegree Equations
Appendix D: Trigonometry
Appendix E: Sigma Notation
Appendix F: Proofs of Theorems
Appendix G: The Logarithm Defined as an Integral
Appendix H: Answers to OddNumbered Exercises
Index
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Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
REFERENCE page 1 Cut here and keep for reference
ALGEBRA
GEOMETRY
Arithmetic Operations
Geometric Formulas a c ad 1 bc 1 − b d bd a a d ad b − 3 − c b c bc d
asb 1 cd − ab 1 ac a1c a c − 1 b b b
Formulas for area A, circumference C, and volume V: Triangle
− 12 ab sin
Exponents and Radicals
a
xm − x m2n xn 1 x2n − n x
x m x n − x m1n sx mdn − x m n
SD
n
x y
sxydn − x n y n
n m n x myn − s x − (s x)
n x 1yn − s x
Î
n n n s xy − s x s y
n
A − r 2
A − 12 r 2
C − 2r
sx x − n y sy n
V−
s − r s in radiansd r
r
b
Sphere m
Sector of Circle
h
¨
xn yn
−
Circle
A − 12 bh
4 3 3 r
¨
s r
Cylinder Cone V − 13 r 2h
V − r 2h
A − 4r 2
A − rsr 2 1 h 2
r
Factoring Special Polynomials
r
x 2 2 y 2 − sx 1 ydsx 2 yd x 3 1 y 3 − sx 1 ydsx 2 2 xy 1 y 2d
r
x 3 2 y 3 − sx 2 ydsx 2 1 xy 1 y 2d
Binomial Theorem
Distance and Midpoint Formulas
sx 1 yd2 − x 2 1 2xy 1 y 2
sx 2 yd2 − x 2 2 2xy 1 y 2
Distance between P1sx1, y1d and P2sx 2, y2d:
sx 1 yd3 − x 3 1 3x 2 y 1 3xy 2 1 y 3
d − ssx 2 2 x1d2 1 s y2 2 y1d2
sx 2 yd3 − x 3 2 3x 2 y 1 3xy 2 2 y 3 sx 1 ydn − x n 1 nx n21y 1
where
SD n k
nsn 2 1d n22 2 x y 2
SD
n n2k k … x y 1 1 nxy n21 1 y n k nsn 2 1d … sn 2 k 1 1d − 1?2?3?…?k
1 … 1
h
h
Midpoint of P1 P2:
m−
y 2 y1 − msx 2 x1d Slopeintercept equation of line with slope m and yintercept b:
If a , b and c . 0, then ca , cb.
y − mx 1 b
If a , b and c , 0, then ca . cb.
     x  . a means x . a or x , 2a
x − a means x − a or x − 2a
y2 2 y1 x 2 2 x1
Pointslope equation of line through P1sx1, y1d with slope m:
If a , b and b , c, then a , c.
If a . 0, then
D
Slope of line through P1sx1, y1d and P2sx 2, y2d:
Inequalities and Absolute Value If a , b, then a 1 c , b 1 c.
x1 1 x 2 y1 1 y2 , 2 2
Lines
Quadratic Formula 2b 6 sb 2 2 4ac If ax 2 1 bx 1 c − 0, then x − . 2a
S
Circles Equation of the circle with center sh, kd and radius r:
x , a means 2a , x , a
sx 2 hd2 1 s y 2 kd2 − r 2
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
REFERENCE page 2 TRIGONOMETRY Angle Measurement
Fundamental Identities csc −
1 sin
sec −
1 cos
tan −
sin cos
cot −
cos sin
s in radiansd
cot −
1 tan
sin2 1 cos2 − 1
Right Angle Trigonometry
1 1 tan2 − sec 2
1 1 cot 2 − csc 2
sins2d − 2sin
coss2d − cos
tans2d − 2tan
sin
radians − 1808 18 −
rad 180
1 rad −
r
180°
¨ r
s − r
opp hyp
csc −
cos −
adj hyp
sec −
hyp adj
tan −
opp adj
cot −
adj opp
sin −
s
hyp opp
hyp
opp
¨ adj
cos
Trigonometric Functions sin −
y r
csc −
x cos − r y tan − x
2 − sin 2
tan
2 − cos 2 2 − cot 2
The Law of Sines
y
r y
S D
S D S D
r sec − x x cot − y
r
B
sin A sin B sin C − − a b c
(x, y)
a
¨
The Law of Cosines
x
b
a 2 − b 2 1 c 2 2 2bc cos A
Graphs of Trigonometric Functions y 1
b 2 − a 2 1 c 2 2 2ac cos B
y y=sin x π
1
2π
y
y=tan x
c 2 − a 2 1 b 2 2 2ab cos C
A
y=cos x 2π
x _1
C
c
π
_1
2π x
π
Addition and Subtraction Formulas x
sinsx 1 yd − sin x cos y 1 cos x sin y sinsx 2 yd − sin x cos y 2 cos x sin y cossx 1 yd − cos x cos y 2 sin x sin y
y
y
y=csc x
y=cot x
cossx 2 yd − cos x cos y 1 sin x sin y
1
1
_1
y
y=sec x
π
2π x
π
_1
2π x
2π x
π
tansx 1 yd −
tan x 1 tan y 1 2 tan x tan y
tansx 2 yd −
tan x 2 tan y 1 1 tan x tan y
DoubleAngle Formulas sin 2x − 2 sin x cos x
Trigonometric Functions of Important Angles radians sin cos tan 08 0 0 1 0 s3y2
s3y3
1y2
s3
308
y6
1y2
458
y4
s2y2
608
y3
908
y2 1 0 —
s3y2
s2y2 1
cos 2x − cos 2x 2 sin 2x − 2 cos 2x 2 1 − 1 2 2 sin 2x tan 2x −
2 tan x 1 2 tan2x
HalfAngle Formulas sin 2x −
1 2 cos 2x 1 1 cos 2x cos 2x − 2 2
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CALCULUS
EARLY TR AN S CE NDE NTA LS NINTH EDITION
Met r i c Ve r si on JAMES STEWART McMASTER UNIVERSITY AND UNIVERSITY OF TORONTO
DANIEL CLEGG PALOMAR COLLEGE
SALEEM WATSON CALIFORNIA STATE UNIVERSITY, LONG BEACH
Australia • Brazil • Mexico • Singapore • United Kingdom • United States
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This is an electronic version of the print textbook. Due to electronic rights restrictions, some third party content may be suppressed. Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. The publisher reserves the right to remove content from this title at any time if subsequent rights restrictions require it. For valuable information on pricing, previous editions, changes to current editions, and alternate formats, please visit www.cengage.com/highered to search by ISBN#, author, title, or keyword for materials in your areas of interest. Important Notice: Media content referenced within the product description or the product text may not be available in the eBook version.
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Calculus: Early Transcendentals, Ninth Edition, Metric Version
© 2021, 2016 Cengage Learning, Inc.
James Stewart, Daniel Clegg, Saleem Watson
ALL RIGHTS RESERVED. No part of this work covered by the copyright herein
Metric Version Prepared by Anthony Tan and Michael Verwer both at McMaster University
permitted by U.S. copyright law, without the prior written permission of the
WCN: 02300 may be reproduced or distributed in any form or by any means, except as copyright owner.
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Contents Preface x A Tribute to James Stewart xxii About the Authors xxiii Technology in the Ninth Edition xxiv To the Student xxv Diagnostic Tests xxvi
A Preview of Calculus 1
1 Functions and Models 1.1 1.2 1.3 1.4 1.5
7
Four Ways to Represent a Function 8 Mathematical Models: A Catalog of Essential Functions 21 New Functions from Old Functions 36 Exponential Functions 45 Inverse Functions and Logarithms 54 Review 67
Principles of Problem Solving 70
2 Limits and Derivatives 2.1 2.2 2.3 2.4 2.5 2.6 2.7
77
The Tangent and Velocity Problems 78 The Limit of a Function 83 Calculating Limits Using the Limit Laws 94 The Precise Definition of a Limit 105 Continuity 115 Limits at Infinity; Horizontal Asymptotes 127 Derivatives and Rates of Change 140 wr i t in g pr oj ec t
• Early Methods for Finding Tangents 152
2.8 The Derivative as a Function 153 Review 166 Problems Plus 171 iii Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
iv
CONTENTS
3 Differentiation Rules
173
3.1 Derivatives of Polynomials and Exponential Functions 174 applied pr oj ec t
• Building a Better Roller Coaster 184
3.2 The Product and Quotient Rules 185 3.3 Derivatives of Trigonometric Functions 191 3.4 The Chain Rule 199 applied pr oj ec t
• Where Should a Pilot Start Descent? 209
3.5 Implicit Differentiation 209 d is cov ery pr oj ec t
• Families of Implicit Curves 217
3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions 217 3.7 Rates of Change in the Natural and Social Sciences 225 3.8 Exponential Growth and Decay 239 applied pr oj ec t
• Controlling Red Blood Cell Loss During Surgery 247
3.9 Related Rates 247 3.10 Linear Approximations and Differentials 254 d is cov ery pr oj ec t
• Polynomial Approximations 260
3.11 Hyperbolic Functions 261 Review 269 Problems Plus 274
4 Applications of Differentiation
279
4.1 Maximum and Minimum Values 280 applied pr oj ec t
• The Calculus of Rainbows 289
4.2 The Mean Value Theorem 290 4.3 What Derivatives Tell Us about the Shape of a Graph 296 4.4 Indeterminate Forms and l’Hospital’s Rule 309 wr itin g pr oj ec t
• The Origins of l’Hospital’s Rule 319
4.5 Summary of Curve Sketching 320 4.6 Graphing with Calculus and Technology 329 4.7 Optimization Problems 336 applied pr oj ec t
• The Shape of a Can 349
applied pr oj ec t
• Planes and Birds: Minimizing Energy 350
4.8 Newton’s Method 351 4.9 Antiderivatives 356 Review 364 Problems Plus 369
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
v
CONTENTS
5 Integrals
371
5.1 The Area and Distance Problems 372 5.2 The Definite Integral 384 d is cov ery pr oj ec t
• Area Functions 398
5.3 The Fundamental Theorem of Calculus 399 5.4 Indefinite Integrals and the Net Change Theorem 409 wr i t in g pr oj ec t
• Newton, Leibniz, and the Invention of Calculus 418
5.5 The Substitution Rule 419 Review 428 Problems Plus 432
6 Applications of Integration
435
6.1 Areas Between Curves 436 applied pr oj ec t
6.2 6.3 6.4 6.5
• The Gini Index 445
Volumes 446 Volumes by Cylindrical Shells 460 Work 467 Average Value of a Function 473 applied pr oj ec t
• Calculus and Baseball 476
applied pr oj ec t
• Where to Sit at the Movies 478
Review 478
Problems Plus 481
7 Techniques of Integration 7.1 7.2 7.3 7.4 7.5 7.6
Integration by Parts 486 Trigonometric Integrals 493 Trigonometric Substitution 500 Integration of Rational Functions by Partial Fractions 507 Strategy for Integration 517 Integration Using Tables and Technology 523 d is cov ery pr oj ec t
• Patterns in Integrals 528
7.7 Approximate Integration 529 7.8 Improper Integrals 542 Review 552 Problems Plus 556
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
485
vi
CONTENTS
8 Further Applications of Integration
559
8.1 Arc Length 560 d is cov ery pr oj ec t
• Arc Length Contest 567
8.2 Area of a Surface of Revolution 567 d is cov ery pr oj ec t
• Rotating on a Slant 575
8.3 Applications to Physics and Engineering 576 d is cov ery pr oj ec t
• Complementary Coffee Cups 587
8.4 Applications to Economics and Biology 587 8.5 Probability 592 Review 600 Problems Plus 602
9 Differential Equations
605
9.1 Modeling with Differential Equations 606 9.2 Direction Fields and Euler’s Method 612 9.3 Separable Equations 621 applied pr oj ec t
• How Fast Does a Tank Drain? 630
9.4 Models for Population Growth 631 9.5 Linear Equations 641 applied pr oj ec t
• Which Is Faster, Going Up or Coming Down? 648
9.6 PredatorPrey Systems 649 Review 656 Problems Plus 659
10 Parametric Equations and Polar Coordinates 10.1
Curves Defined by Parametric Equations 662
10.2
Calculus with Parametric Curves 673
d is cov ery pr oj ec t
d is cov ery pr oj ec t
10.3
• Running Circles Around Circles 672 • Bézier Curves 684
Polar Coordinates 684 d is cov ery pr oj ec t
10.4 10.5
661
• Families of Polar Curves 694
Calculus in Polar Coordinates 694 Conic Sections 702
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CONTENTS
10.6
vii
Conic Sections in Polar Coordinates 711 Review 719
Problems Plus 722
11 Sequences, Series, and Power Series 11.1
Sequences 724 d is cov ery pr oj ec t
11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 11.10
723
• Logistic Sequences 738
Series 738 The Integral Test and Estimates of Sums 751 The Comparison Tests 760 Alternating Series and Absolute Convergence 765 The Ratio and Root Tests 774 Strategy for Testing Series 779 Power Series 781 Representations of Functions as Power Series 787 Taylor and Maclaurin Series 795 d is cov ery pr oj ec t wr i t in g pr oj ec t
• An Elusive Limit 810
• How Newton Discovered the Binomial Series 811
11.11 Applications of Taylor Polynomials 811 applied pr oj ec t
• Radiation from the Stars 820
Review 821
Problems Plus 825
12 Vectors and the Geometry of Space 12.1 12.2
ThreeDimensional Coordinate Systems 830 Vectors 836 d is cov ery pr oj ec t
12.3 12.4
• The Shape of a Hanging Chain 846
The Dot Product 847 The Cross Product 855 d is cov ery pr oj ec t
• The Geometry of a Tetrahedron 864
12.5
Equations of Lines and Planes 864
12.6
Cylinders and Quadric Surfaces 875 Review 883
d is cov ery pr oj ec t
• Putting 3D in Perspective 874
Problems Plus 887
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
829
viii
CONTENTS
13 Vector Functions 13.1 13.2 13.3 13.4
Vector Functions and Space Curves 890 Derivatives and Integrals of Vector Functions 898 Arc Length and Curvature 904 Motion in Space: Velocity and Acceleration 916 applied pr oj ec t
889
• Kepler’s Laws 925
Review 927
Problems Plus 930
14 Partial Derivatives
933
14.1 14.2 14.3
Functions of Several Variables 934 Limits and Continuity 951 Partial Derivatives 961
14.4
Tangent Planes and Linear Approximations 974
d is cov ery pr oj ec t
applied pr oj ec t
14.5 14.6 14.7
• The Speedo LZR Racer 984
The Chain Rule 985 Directional Derivatives and the Gradient Vector 994 Maximum and Minimum Values 1008 d is cov ery pr oj ec t
14.8
• Deriving the CobbDouglas Production Function 973
• Quadratic Approximations and Critical Points 1019
Lagrange Multipliers 1020 applied pr oj ec t
• Rocket Science 1028
applied pr oj ec t
• HydroTurbine Optimization 1030
Review 1031
Problems Plus 1035
15 Multiple Integrals 15.1 15.2 15.3 15.4 15.5 15.6
Double Integrals over Rectangles 1038 Double Integrals over General Regions 1051 Double Integrals in Polar Coordinates 1062 Applications of Double Integrals 1069 Surface Area 1079 Triple Integrals 1082 d is cov ery pr oj ec t
15.7
1037
• Volumes of Hyperspheres 1095
Triple Integrals in Cylindrical Coordinates 1095 d is cov ery pr oj ec t
• The Intersection of Three Cylinders 1101
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
ix
CONTENTS
15.8
Triple Integrals in Spherical Coordinates 1102
15.9
Change of Variables in Multiple Integrals 1109 Review 1117
applied pr oj ec t
• Roller Derby 1108
Problems Plus 1121
16 Vector Calculus 16.1 16.2 16.3 16.4 16.5 16.6 16.7 16.8 16.9 16.10
1123
Vector Fields 1124 Line Integrals 1131 The Fundamental Theorem for Line Integrals 1144 Green’s Theorem 1154 Curl and Divergence 1161 Parametric Surfaces and Their Areas 1170 Surface Integrals 1182 Stokes’ Theorem 1195 The Divergence Theorem 1201 Summary 1208 Review 1209
Problems Plus 1213
Appendixes A B C D E F G H
Numbers, Inequalities, and Absolute Values A2 Coordinate Geometry and Lines A10 Graphs of SecondDegree Equations A16 Trigonometry A24 Sigma Notation A36 Proofs of Theorems A41 The Logarithm Defined as an Integral A53 Answers to OddNumbered Exercises A61
Index A143
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
A1
Preface A great discovery solves a great problem but there is a grain of discovery in the solution of any problem. Your problem may be modest; but if it challenges your curiosity and brings into play your inventive faculties, and if you solve it by your own means, you may experience the tension and enjoy the triumph of discovery. george polya
The art of teaching, Mark Van Doren said, is the art of assisting discovery. In this Ninth Edition, Metric Version, as in all of the preceding editions, we continue the tradition of writing a book that, we hope, assists students in discovering calculus — both for its practical power and its surprising beauty. We aim to convey to the student a sense of the utility of calculus as well as to promote development of technical ability. At the same time, we strive to give some appreciation for the intrinsic beauty of the subject. Newton undoubtedly experienced a sense of triumph when he made his great discoveries. We want students to share some of that excitement. The emphasis is on understanding concepts. Nearly all calculus instructors agree that conceptual understanding should be the ultimate goal of calculus instruction; to implement this goal we present fundamental topics graphically, numerically, algebraically, and verbally, with an emphasis on the relationships between these different representations. Visualization, numerical and graphical experimentation, and verbal descriptions can greatly facilitate conceptual understanding. Moreover, conceptual understanding and technical skill can go hand in hand, each reinforcing the other. We are keenly aware that good teaching comes in different forms and that there are different approaches to teaching and learning calculus, so the exposition and exercises are designed to accommodate different teaching and learning styles. The features (including projects, extended exercises, principles of problem solving, and historical insights) provide a variety of enhancements to a central core of fundamental concepts and skills. Our aim is to provide instructors and their students with the tools they need to chart their own paths to discovering calculus.
Alternate Versions The Stewart Calculus series includes several other calculus textbooks that might be preferable for some instructors. Most of them also come in single variable and multivariable versions.
• Calculus, Ninth Edition, Metric Version, is similar to the present textbook except that the exponential, logarithmic, and inverse trigonometric functions are covered after the chapter on integration.
• Essential Calculus, Second Edition, is a much briefer book (840 pages), though it contains almost all of the topics in Calculus, Ninth Edition. The relative brevity is achieved through briefer exposition of some topics and putting some features on the website. x Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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• Essential Calculus: Early Transcendentals, Second Edition, resembles Essential Calculus, but the exponential, logarithmic, and inverse trigonometric functions are covered in Chapter 3.
• Calculus: Concepts and Contexts, Fourth Edition, emphasizes conceptual understanding even more strongly than this book. The coverage of topics is not encyclopedic and the material on transcendental functions and on parametric equations is woven throughout the book instead of being treated in separate chapters.
• Brief Applied Calculus is intended for students in business, the social sciences, and the life sciences.
• Biocalculus: Calculus for the Life Sciences is intended to show students in the life sciences how calculus relates to biology.
• Biocalculus: Calculus, Probability, and Statistics for the Life Sciences contains all the content of Biocalculus: Calculus for the Life Sciences as well as three additional chapters covering probability and statistics.
What’s New in the Ninth Edition, Metric Version? The overall structure of the text remains largely the same, but we have made many improvements that are intended to make the Ninth Edition, Metric Version even more usable as a teaching tool for instructors and as a learning tool for students. The changes are a result of conversations with our colleagues and students, suggestions from users and reviewers, insights gained from our own experiences teaching from the book, and from the copious notes that James Stewart entrusted to us about changes that he wanted us to consider for the new edition. In all the changes, both small and large, we have retained the features and tone that have contributed to the success of this book.
• More than 20% of the exercises are new: Basic exercises have been added, where appropriate, near the beginning of exercise sets. These exercises are intended to build student confidence and reinforce understanding of the fundamental concepts of a section. (See, for instance, Exercises 7.3.1 – 4, 9.1.1 – 5, 11.4.3 – 6.) Some new exercises include graphs intended to encourage students to understand how a graph facilitates the solution of a problem; these exercises complement subsequent exercises in which students need to supply their own graph. (See Exercises 6.2.1– 4, Exercises 10.4.43 – 46 as well as 53 – 54, 15.5.1 – 2, 15.6.9 – 12, 16.7.15 and 24, 16.8.9 and 13.) Some exercises have been structured in two stages, where part (a) asks for the setup and part (b) is the evaluation. This allows students to check their answer to part (a) before completing the problem. (See Exercises 6.1.1 – 4, 6.3.3 – 4, 15.2.7 – 10.) Some challenging and extended exercises have been added toward the end of selected exercise sets (such as Exercises 6.2.87, 9.3.56, 11.2.79 – 81, and 11.9.47). Titles have been added to selected exercises when the exercise extends a concept discussed in the section. (See, for example, Exercises 2.6.66, 10.1.55 – 57, 15.2.80 – 81.) Some of our favorite new exercises are 1.3.71, 3.4.99, 3.5.65, 4.5.55 – 58, 6.2.79, 6.5.18, 10.5.69, 15.1.38, and 15.4.3 – 4. In addition, Problem 14 in the Problems Plus following Chapter 6 and Problem 4 in the Problems Plus following Chapter 15 are interesting and challenging. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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• New examples have been added, and additional steps have been added to the solutions of some existing examples. (See, for instance, Example 2.7.5, Example 6.3.5, Example 10.1.5, Examples 14.8.1 and 14.8.4, and Example 16.3.4.)
• Several sections have been restructured and new subheads added to focus the organization around key concepts. (Good illustrations of this are Sections 2.3, 11.1, 11.2, and 14.2.)
• Many new graphs and illustrations have been added, and existing ones updated, to provide additional graphical insights into key concepts.
• A few new topics have been added and others expanded (within a section or in extended exercises) that were requested by reviewers. (Examples include a subsection on torsion in Section 13.3, symmetric difference quotients in Exercise 2.7.60, and improper integrals of more than one type in Exercises 7.8.65 – 68.)
• New projects have been added and some existing projects have been updated. (For instance, see the Discovery Project following Section 12.2, The Shape of a Hanging Chain.)
• Derivatives of logarithmic functions and inverse trigonometric functions are now covered in one section (3.6) that emphasizes the concept of the derivative of an inverse function.
• A lternating series and absolute convergence are now covered in one section (11.5). • The chapter on SecondOrder Differential Equations, as well as the associated appendix section on complex numbers, has been moved to the website.
Features Each feature is designed to complement different teaching and learning practices. Throughout the text there are historical insights, extended exercises, projects, problemsolving principles, and many opportunities to experiment with concepts by using technology. We are mindful that there is rarely enough time in a semester to utilize all of these features, but their availability in the book gives the instructor the option to assign some and perhaps simply draw attention to others in order to emphasize the rich ideas of calculus and its crucial importance in the real world.
n Conceptual Exercises The most important way to foster conceptual understanding is through the problems that the instructor assigns. To that end we have included various types of problems. Some exercise sets begin with requests to explain the meanings of the basic concepts of the section (see, for instance, the first few exercises in Sections 2.2, 2.5, 11.2, 14.2, and 14.3) and most exercise sets contain exercises designed to reinforce basic understanding (such as Exercises 2.5.3 – 10, 5.5.1 – 8, 6.1.1 – 4, 7.3.1 – 4, 9.1.1 – 5, and 11.4.3 – 6). Other exercises test conceptual understanding through graphs or tables (see Exercises 2.7.17, 2.8.36 – 38, 2.8.47 – 52, 9.1.23 – 25, 10.1.30 – 33, 13.2.1 – 2, 13.3.37 – 43, 14.1.41 – 44, 14.3.2, 14.3.4 – 6, 14.6.1 – 2, 14.7.3 – 4, 15.1.6 – 8, 16.1.13 – 22, 16.2.19 – 20, and 16.3.1 – 2). Many exercises provide a graph to aid in visualization (see for instance Exercises 6.2.1 – 4, 10.4.43 – 46, 15.5.1 – 2, 15.6.9 – 12, and 16.7.24). Another type of exercise uses verbal descriptions to gauge conceptual understanding (see Exercises 2.5.12, 2.8.66, 4.3.79 – 80, and 7.8.79). In addition, all the review sections begin with a Concept Check and a TrueFalse Quiz. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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We particularly value problems that combine and compare graphical, numerical, and algebraic approaches (see Exercises 2.6.45 – 46, 3.7.29, and 9.4.4).
n Graded Exercise Sets Each exercise set is carefully graded, progressing from basic conceptual exercises, to skilldevelopment and graphical exercises, and then to more challenging exercises that often extend the concepts of the section, draw on concepts from previous sections, or involve applications or proofs.
n RealWorld Data Realworld data provide a tangible way to introduce, motivate, or illustrate the concepts of calculus. As a result, many of the examples and exercises deal with functions defined by such numerical data or graphs. These realworld data have been obtained by contacting companies and government agencies as well as researching on the Internet and in libraries. See, for instance, Figure 1 in Section 1.1 (seismograms from the Northridge earthquake), Exercise 2.8.36 (number of cosmetic surgeries), Exercise 5.1.12 (velocity of the space shuttle Endeavour), Exercise 5.4.83 (power consumption in the New England states), Example 3 in Section 14.4 (the heat index), Figure 1 in Section 14.6 (temperature contour map), Example 9 in Section 15.1 (snowfall in Colorado), and Figure 1 in Section 16.1 (velocity vector fields of wind in San Francisco Bay).
n Projects One way of involving students and making them active learners is to have them work (perhaps in groups) on extended projects that give a feeling of substantial accomplishment when completed. There are three kinds of projects in the text. Applied Projects involve applications that are designed to appeal to the imagination of students. The project after Section 9.5 asks whether a ball thrown upward takes longer to reach its maximum height or to fall back to its original height (the answer might surprise you). The project after Section 14.8 uses Lagrange multipliers to determine the masses of the three stages of a rocket so as to minimize the total mass while enabling the rocket to reach a desired velocity. Discovery Projects anticipate results to be discussed later or encourage discovery through pattern recognition (see the project following Section 7.6, which explores patterns in integrals). Other discovery projects explore aspects of geometry: tetrahedra (after Section 12.4), hyperspheres (after Section 15.6), and intersections of three cylinders (after Section 15.7). Additionally, the project following Section 12.2 uses the geometric definition of the derivative to find a formula for the shape of a hanging chain. Some projects make substantial use of technology; the one following Section 10.2 shows how to use Bézier curves to design shapes that represent letters for a laser printer. Writing Projects ask students to compare presentday methods with those of the founders of calculus — Fermat’s method for finding tangents, for instance, following Section 2.7. Suggested references are supplied. More projects can be found in the Instructor’s Guide. There are also extended exercises that can serve as smaller projects. (See Exercise 4.7.53 on the geometry of beehive cells, Exercise 6.2.87 on scaling solids of revolution, or Exercise 9.3.56 on the formation of sea ice.)
n Problem Solving Students usually have difficulties with problems that have no single welldefined procedure for obtaining the answer. As a student of George Polya, James Stewart
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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experienced firsthand Polya’s delightful and penetrating insights into the process of problem solving. Accordingly, a modified version of Polya’s fourstage problemsolving strategy is presented following Chapter 1 in Principles of Problem Solving. These principles are applied, both explicitly and implicitly, throughout the book. Each of the other chapters is followed by a section called Problems Plus, which features examples of how to tackle challenging calculus problems. In selecting the Problems Plus problems we have kept in mind the following advice from David Hilbert: “A mathematical problem should be difficult in order to entice us, yet not inaccessible lest it mock our efforts.” We have used these problems to great effect in our own calculus classes; it is gratifying to see how students respond to a challenge. James Stewart said, “When I put these challenging problems on assignments and tests I grade them in a different way . . . I reward a student significantly for ideas toward a solution and for recognizing which problemsolving principles are relevant.”
n Technology When using technology, it is particularly important to clearly understand the concepts that underlie the images on the screen or the results of a calculation. When properly used, graphing calculators and computers are powerful tools for discovering and understanding those concepts. This textbook can be used either with or without technology — we use two special symbols to indicate clearly when a particular type of assistance from technology is required. The icon ; indicates an exercise that definitely requires the use of graphing software or a graphing calculator to aid in sketching a graph. (That is not to say that the technology can’t be used on the other exercises as well.) The symbol means that the assistance of software or a graphing calculator is needed beyond just graphing to complete the exercise. Freely available websites such as WolframAlpha.com or Symbolab.com are often suitable. In cases where the full resources of a computer algebra system, such as Maple or Mathematica, are needed, we state this in the exercise. Of course, technology doesn’t make pencil and paper obsolete. Hand calculation and sketches are often preferable to technology for illustrating and reinforcing some concepts. Both instructors and students need to develop the ability to decide where using technology is appropriate and where more insight is gained by working out an exercise by hand.
n WebAssign: webassign.net This Ninth Edition is available with WebAssign, a fully customizable online solution for STEM disciplines from Cengage. WebAssign includes homework, an interactive mobile eBook, videos, tutorials and Explore It interactive learning modules. Instructors can decide what type of help students can access, and when, while working on assignments. The patented grading engine provides unparalleled answer evaluation, giving students instant feedback, and insightful analytics highlight exactly where students are struggling. For more information, visit cengage.com/WebAssign.
n Stewart Website Visit StewartCalculus.com for these additional materials:
• • • • •
Homework Hints Solutions to the Concept Checks (from the review section of each chapter) Algebra and Analytic Geometry Review Lies My Calculator and Computer Told Me History of Mathematics, with links to recommended historical websites
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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• Additional Topics (complete with exercise sets): Fourier Series, Rotation of Axes, Formulas for the Remainder Theorem in Taylor Series
• Additional chapter on secondorder differential equations, including the method of series solutions, and an appendix section reviewing complex numbers and complex exponential functions
• Instructor Area that includes archived problems (drill exercises that appeared in previous editions, together with their solutions)
• Challenge Problems (some from the Problems Plus sections from prior editions) • Links, for particular topics, to outside Web resources
Content
Diagnostic Tests
The book begins with four diagnostic tests, in Basic Algebra, Analytic Geometry, Functions, and Trigonometry.
A Preview of Calculus
This is an overview of the subject and includes a list of questions to motivate the study of calculus.
1 Functions and Models
From the beginning, multiple representations of functions are stressed: verbal, numerical, visual, and algebraic. A discussion of mathematical models leads to a review of the standard functions, including exponential and logarithmic functions, from these four points of view.
2 Limits and Derivatives
The material on limits is motivated by a prior discussion of the tangent and velocity problems. Limits are treated from descriptive, graphical, numerical, and algebraic points of view. Section 2.4, on the precise definition of a limit, is an optional section. Sections 2.7 and 2.8 deal with derivatives (including derivatives for functions defined graphically and numerically) before the differentiation rules are covered in Chapter 3. Here the examples and exercises explore the meaning of derivatives in various contexts. Higher derivatives are introduced in Section 2.8.
3 Differentiation Rules
All the basic functions, including exponential, logarithmic, and inverse trigonometric functions, are differentiated here. The latter two classes of functions are now covered in one section that focuses on the derivative of an inverse function. When derivatives are computed in applied situations, students are asked to explain their meanings. Exponential growth and decay are included in this chapter.
4 Applications of Differentiation
The basic facts concerning extreme values and shapes of curves are deduced from the Mean Value Theorem. Graphing with technology emphasizes the interaction between calculus and machines and the analysis of families of curves. Some substantial optimization problems are provided, including an explanation of why you need to raise your head 42° to see the top of a rainbow.
5 Integrals
The area problem and the distance problem serve to motivate the definite integral, with sigma notation introduced as needed. (Full coverage of sigma notation is provided in Appendix E.) Emphasis is placed on explaining the meanings of integrals in various contexts and on estimating their values from graphs and tables.
6 Applications of Integration
This chapter presents the applications of integration — area, volume, work, average value — that can reasonably be done without specialized techniques of integration. General methods are emphasized. The goal is for students to be able to divide a quantity into small pieces, estimate with Riemann sums, and recognize the limit as an integral.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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7 Techniques of Integration
All the standard methods are covered but, of course, the real challenge is to be able to recognize which technique is best used in a given situation. Accordingly, a strategy for evaluating integrals is explained in Section 7.5. The use of mathematical software is discussed in Section 7.6.
8 Further Applications of Integration This chapter contains the applications of integration — arc length and surface area — for
which it is useful to have available all the techniques of integration, as well as applications to biology, economics, and physics (hydrostatic force and centers of mass). A section on probability is included. There are more applications here than can realistically be covered in a given course. Instructors may select applications suitable for their students and for which they themselves have enthusiasm.
9 Differential Equations
Modeling is the theme that unifies this introductory treatment of differential equations. Direction fields and Euler’s method are studied before separable and linear equations are solved explicitly, so that qualitative, numerical, and analytic approaches are given equal consideration. These methods are applied to the exponential, logistic, and other models for population growth. The first four or five sections of this chapter serve as a good introduction to firstorder differential equations. An optional final section uses predatorprey models to illustrate systems of differential equations.
10 Parametric Equations and Polar Coordinates
This chapter introduces parametric and polar curves and applies the methods of calculus to them. Parametric curves are well suited to projects that require graphing with technology; the two presented here involve families of curves and Bézier curves. A brief treatment of conic sections in polar coordinates prepares the way for Kepler’s Laws in Chapter 13.
11 Sequences, Series, and Power Series
The convergence tests have intuitive justifications (see Section 11.3) as well as formal proofs. Numerical estimates of sums of series are based on which test was used to prove convergence. The emphasis is on Taylor series and polynomials and their applications to physics.
12 Vectors and the Geometry of Space
The material on threedimensional analytic geometry and vectors is covered in this and the next chapter. Here we deal with vectors, the dot and cross products, lines, planes, and surfaces.
13 Vector Functions
This chapter covers vectorvalued functions, their derivatives and integrals, the length and curvature of space curves, and velocity and acceleration along space curves, culminating in Kepler’s laws.
14 Partial Derivatives
Functions of two or more variables are studied from verbal, numerical, visual, and algebraic points of view. In particular, partial derivatives are introduced by looking at a specific column in a table of values of the heat index (perceived air temperature) as a function of the actual temperature and the relative humidity.
15 Multiple Integrals
Contour maps and the Midpoint Rule are used to estimate the average snowfall and average temperature in given regions. Double and triple integrals are used to compute volumes, surface areas, and (in projects) volumes of hyperspheres and volumes of intersections of three cylinders. Cylindrical and spherical coordinates are introduced in the context of evaluating triple integrals. Several applications are considered, including computing mass, charge, and probabilities.
16 Vector Calculus
Vector fields are introduced through pictures of velocity fields showing San Francisco Bay wind patterns. The similarities among the Fundamental Theorem for line integrals, Green’s Theorem, Stokes’ Theorem, and the Divergence Theorem are emphasized.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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17 SecondOrder Differential Equations
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Since firstorder differential equations are covered in Chapter 9, this online chapter deals with secondorder linear differential equations, their application to vibrating springs and electric circuits, and series solutions.
Ancillaries Calculus, Early Transcendentals, Ninth Edition, Metric Version, is supported by a complete set of ancillaries. Each piece has been designed to enhance student understanding and to facilitate creative instruction.
n Ancillaries for Instructors Instructor’s Guide
by Douglas Shaw
Each section of the text is discussed from several viewpoints. Available online at the Instructor’s Companion Site, the Instructor’s Guide contains suggested time to allot, points to stress, text discussion topics, core materials for lecture, workshop / discussion suggestions, group work exercises in a form suitable for handout, and suggested homework assignments.
Complete Solutions Manual
Single Variable Calculus: Early Transcendentals, Ninth Edition, Metric Version Chapters 1–11 By Joshua Babbin, Scott Barnett, and Jeffery A. Cole, with metrication by Anthony Tan and Michael Verwer, both from McMaster University.
Multivariable Calculus, Ninth Edition, Metric Version Chapters 10 –16 By Joshua Babbin and Gina Sanders, with metrication by Anthony Tan and Michael Verwer, both from McMaster University. Includes workedout solutions to all exercises in the text. Both volumes of the Complete Solutions Manual are available online at the Instructor’s Companion Site.
Test Bank Contains textspecific multiplechoice and free response test items and is available online at the Instructor’s Companion Site. Cengage Learning Testing Powered by Cognero
This flexible online system allows you to author, edit, and manage test bank content; create multiple test versions in an instant; and deliver tests from your LMS, your classroom, or wherever you want.
n Ancillaries for Instructors and Students Stewart Website StewartCalculus.com
Homework Hints n Algebra Review n Additional Topics n Drill exercises Challenge Problems n Web links n History of Mathematics
WebAssign®
Access to WebAssign Printed Access Code: ISBN 9780357439166 Instant Access Code: ISBN 9780357439159
Prepare for class with confidence using WebAssign from Cengage. This online learning platform—which includes an interactive ebook—fuels practice, so you absorb what you learn and prepare better for tests. Videos and tutorials walk you through concepts and deliver instant feedback and grading, so you always know where you stand in class. Focus your study time and get extra practice where you need it most. Study smarter! Ask your instructor today how you can get access to WebAssign, or learn about selfstudy options at Cengage.com/WebAssign.
n
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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Acknowledgments One of the main factors aiding in the preparation of this edition is the cogent advice from a large number of reviewers, all of whom have extensive experience teaching calculus. We greatly appreciate their suggestions and the time they spent to understand the approach taken in this book. We have learned something from each of them.
n Ninth Edition Reviewers Malcolm Adams, University of Georgia Ulrich Albrecht, Auburn University Bonnie Amende, Saint Martin’s University Champike Attanayake, Miami University Middletown Amy Austin, Texas A&M University Elizabeth Bowman, University of Alabama Joe Brandell, West Bloomfield High School / Oakland University Lorraine Braselton, Georgia Southern University Mark Brittenham, University of Nebraska – Lincoln Michael Ching, Amherst College KwaiLee Chui, University of Florida Arman Darbinyan, Vanderbilt University Roger Day, Illinois State University Toka Diagana, Howard University Karamatu Djima, Amherst College Mark Dunster, San Diego State University Eric Erdmann, University of Minnesota – Duluth Debra Etheridge, The University of North Carolina at Chapel Hill Jerome Giles, San Diego State University Mark Grinshpon, Georgia State University Katie Gurski, Howard University John Hall, Yale University David Hemmer, University at Buffalo – SUNY, N. Campus Frederick Hoffman, Florida Atlantic University Keith Howard, Mercer University Iztok Hozo, Indiana University Northwest ShuJen Huang, University of Florida Matthew Isom, Arizona State University – Polytechnic James Kimball, University of Louisiana at Lafayette Thomas Kinzel, Boise State University Anastasios Liakos, United States Naval Academy Chris Lim, Rutgers University – Camden Jia Liu, University of West Florida Joseph Londino, University of Memphis
Colton Magnant, Georgia Southern University Mark Marino, University at Buffalo – SUNY, N. Campus Kodie Paul McNamara, Georgetown University Mariana Montiel, Georgia State University Russell Murray, Saint Louis Community College Ashley Nicoloff, Glendale Community College Daniella NokolovaPopova, Florida Atlantic University Giray Okten, Florida State University – Tallahassee Aaron Peterson, Northwestern University Alice Petillo, Marymount University Mihaela Poplicher, University of Cincinnati Cindy Pulley, Illinois State University Russell Richins, Thiel College Lorenzo Sadun, University of Texas at Austin Michael Santilli, Mesa Community College Christopher Shaw, Columbia College Brian Shay, Canyon Crest Academy Mike Shirazi, Germanna Community College – Fredericksburg Pavel Sikorskii, Michigan State University Mary Smeal, University of Alabama Edwin Smith, Jacksonville State University Sandra Spiroff, University of Mississippi Stan Stascinsky, Tarrant County College Jinyuan Tao, Loyola University of Maryland Ilham Tayahi, University of Memphis Michael Tom, Louisiana State University – Baton Rouge Michael Westmoreland, Denison University Scott Wilde, Baylor University Larissa Williamson, University of Florida Michael Yatauro, Penn State Brandywine Gang Yu, Kent State University Loris Zucca, Lone Star College – Kingwood
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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n Previous Edition Reviewers Jay Abramson, Arizona State University B. D. Aggarwala, University of Calgary John Alberghini, Manchester Community College Michael Albert, CarnegieMellon University Daniel Anderson, University of Iowa Maria Andersen, Muskegon Community College Eric Aurand, Eastfield College Amy Austin, Texas A&M University Donna J. Bailey, Northeast Missouri State University Wayne Barber, Chemeketa Community College Joy Becker, University of Wisconsin – Stout Marilyn Belkin, Villanova University Neil Berger, University of Illinois, Chicago David Berman, University of New Orleans Anthony J. Bevelacqua, University of North Dakota Richard Biggs, University of Western Ontario Robert Blumenthal, Oglethorpe University Martina Bode, Northwestern University Przemyslaw Bogacki, Old Dominion University Barbara Bohannon, Hofstra University Jay Bourland, Colorado State University Adam Bowers, University of California San Diego Philip L. Bowers, Florida State University Amy Elizabeth Bowman, University of Alabama in Huntsville Stephen W. Brady, Wichita State University Michael Breen, Tennessee Technological University Monica Brown, University of Missouri – St. Louis Robert N. Bryan, University of Western Ontario David Buchthal, University of Akron Roxanne Byrne, University of Colorado at Denver and Health Sciences Center Jenna Carpenter, Louisiana Tech University Jorge Cassio, MiamiDade Community College Jack Ceder, University of California, Santa Barbara Scott Chapman, Trinity University ZhenQing Chen, University of Washington – Seattle James Choike, Oklahoma State University Neena Chopra, The Pennsylvania State University Teri Christiansen, University of Missouri – Columbia Barbara Cortzen, DePaul University Carl Cowen, Purdue University Philip S. Crooke, Vanderbilt University Charles N. Curtis, Missouri Southern State College Daniel Cyphert, Armstrong State College Robert Dahlin Bobby Dale Daniel, Lamar University Jennifer Daniel, Lamar University M. Hilary Davies, University of Alaska Anchorage Gregory J. Davis, University of Wisconsin – Green Bay Elias Deeba, University of Houston – Downtown Daniel DiMaria, Suffolk Community College Seymour Ditor, University of Western Ontario Edward Dobson, Mississippi State University Andras Domokos, California State University, Sacramento Greg Dresden, Washington and Lee University
Daniel Drucker, Wayne State University Kenn Dunn, Dalhousie University Dennis Dunninger, Michigan State University Bruce Edwards, University of Florida David Ellis, San Francisco State University John Ellison, Grove City College Martin Erickson, Truman State University Garret Etgen, University of Houston Theodore G. Faticoni, Fordham University Laurene V. Fausett, Georgia Southern University Norman Feldman, Sonoma State University Le Baron O. Ferguson, University of California – Riverside Newman Fisher, San Francisco State University Timothy Flaherty, Carnegie Mellon University José D. Flores, The University of South Dakota William Francis, Michigan Technological University James T. Franklin, Valencia Community College, East Stanley Friedlander, Bronx Community College Patrick Gallagher, Columbia University – New York Paul Garrett, University of Minnesota – Minneapolis Frederick Gass, Miami University of Ohio Lee Gibson, University of Louisville Bruce Gilligan, University of Regina Matthias K. Gobbert, University of Maryland, Baltimore County Gerald Goff, Oklahoma State University Isaac Goldbring, University of Illinois at Chicago Jane Golden, Hillsborough Community College Stuart Goldenberg, California Polytechnic State University John A. Graham, Buckingham Browne & Nichols School Richard Grassl, University of New Mexico Michael Gregory, University of North Dakota Charles Groetsch, University of Cincinnati Semion Gutman, University of Oklahoma Paul Triantafilos Hadavas, Armstrong Atlantic State University Salim M. Haïdar, Grand Valley State University D. W. Hall, Michigan State University Robert L. Hall, University of Wisconsin – Milwaukee Howard B. Hamilton, California State University, Sacramento Darel Hardy, Colorado State University Shari Harris, John Wood Community College Gary W. Harrison, College of Charleston Melvin Hausner, New York University/Courant Institute Curtis Herink, Mercer University Russell Herman, University of North Carolina at Wilmington Allen Hesse, Rochester Community College Diane Hoffoss, University of San Diego Randall R. Holmes, Auburn University Lorraine Hughes, Mississippi State University James F. Hurley, University of Connecticut Amer Iqbal, University of Washington – Seattle Matthew A. Isom, Arizona State University Jay Jahangiri, Kent State University Gerald Janusz, University of Illinois at UrbanaChampaign John H. Jenkins, EmbryRiddle Aeronautical University, Prescott Campus
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
xx
PREFACE
Lea Jenkins, Clemson University John Jernigan, Community College of Philadelphia Clement Jeske, University of Wisconsin, Platteville Carl Jockusch, University of Illinois at UrbanaChampaign Jan E. H. Johansson, University of Vermont Jerry Johnson, Oklahoma State University Zsuzsanna M. Kadas, St. Michael’s College Brian Karasek, South Mountain Community College Nets Katz, Indiana University Bloomington Matt Kaufman Matthias Kawski, Arizona State University Frederick W. Keene, Pasadena City College Robert L. Kelley, University of Miami Akhtar Khan, Rochester Institute of Technology Marianne Korten, Kansas State University Virgil Kowalik, Texas A&I University Jason Kozinski, University of Florida Kevin Kreider, University of Akron Leonard Krop, DePaul University Carole Krueger, The University of Texas at Arlington Mark Krusemeyer, Carleton College Ken Kubota, University of Kentucky John C. Lawlor, University of Vermont Christopher C. Leary, State University of New York at Geneseo David Leeming, University of Victoria Sam Lesseig, Northeast Missouri State University Phil Locke, University of Maine Joyce Longman, Villanova University Joan McCarter, Arizona State University Phil McCartney, Northern Kentucky University Igor Malyshev, San Jose State University Larry Mansfield, Queens College Mary Martin, Colgate University Nathaniel F. G. Martin, University of Virginia Gerald Y. Matsumoto, American River College James McKinney, California State Polytechnic University, Pomona Tom Metzger, University of Pittsburgh Richard Millspaugh, University of North Dakota John Mitchell, Clark College Lon H. Mitchell, Virginia Commonwealth University Michael Montaño, Riverside Community College Teri Jo Murphy, University of Oklahoma Martin Nakashima, California State Polytechnic University, Pomona Ho Kuen Ng, San Jose State University Richard Nowakowski, Dalhousie University Hussain S. Nur, California State University, Fresno Norma OrtizRobinson, Virginia Commonwealth University Wayne N. Palmer, Utica College Vincent Panico, University of the Pacific F. J. Papp, University of Michigan – Dearborn Donald Paul, Tulsa Community College Mike Penna, Indiana University – Purdue University Indianapolis Chad Pierson, University of Minnesota, Duluth Mark Pinsky, Northwestern University Lanita Presson, University of Alabama in Huntsville
Lothar Redlin, The Pennsylvania State University Karin Reinhold, State University of New York at Albany Thomas Riedel, University of Louisville Joel W. Robbin, University of Wisconsin – Madison Lila Roberts, Georgia College and State University E. Arthur Robinson, Jr., The George Washington University Richard Rockwell, Pacific Union College Rob Root, Lafayette College Richard Ruedemann, Arizona State University David Ryeburn, Simon Fraser University Richard St. Andre, Central Michigan University Ricardo Salinas, San Antonio College Robert Schmidt, South Dakota State University Eric Schreiner, Western Michigan University Christopher Schroeder, Morehead State University Mihr J. Shah, Kent State University – Trumbull Angela Sharp, University of Minnesota, Duluth Patricia Shaw, Mississippi State University Qin Sheng, Baylor University Theodore Shifrin, University of Georgia Wayne Skrapek, University of Saskatchewan Larry Small, Los Angeles Pierce College Teresa Morgan Smith, Blinn College William Smith, University of North Carolina Donald W. Solomon, University of Wisconsin – Milwaukee Carl Spitznagel, John Carroll University Edward Spitznagel, Washington University Joseph Stampfli, Indiana University Kristin Stoley, Blinn College Mohammad Tabanjeh, Virginia State University Capt. Koichi Takagi, United States Naval Academy M. B. Tavakoli, Chaffey College Lorna TenEyck, Chemeketa Community College Magdalena Toda, Texas Tech University Ruth Trygstad, Salt Lake Community College Paul Xavier Uhlig, St. Mary’s University, San Antonio Stan Ver Nooy, University of Oregon Andrei Verona, California State University – Los Angeles Klaus Volpert, Villanova University Rebecca Wahl, Butler University Russell C. Walker, CarnegieMellon University William L. Walton, McCallie School Peiyong Wang, Wayne State University Jack Weiner, University of Guelph Alan Weinstein, University of California, Berkeley Roger Werbylo, Pima Community College Theodore W. Wilcox, Rochester Institute of Technology Steven Willard, University of Alberta David Williams, Clayton State University Robert Wilson, University of Wisconsin – Madison Jerome Wolbert, University of Michigan – Ann Arbor Dennis H. Wortman, University of Massachusetts, Boston Mary Wright, Southern Illinois University – Carbondale Paul M. Wright, Austin Community College Xian Wu, University of South Carolina Zhuan Ye, Northern Illinois University
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
PREFACE
xxi
We thank all those who have contributed to this edition—and there are many—as well as those whose input in previous editions lives on in this new edition. We thank Marigold Ardren, David Behrman, George Bergman, R. B. Burckel, Bruce Colletti, John Dersch, Gove Effinger, Bill Emerson, Alfonso GraciaSaz, Jeffery Hayen, Dan Kalman, Quyan Khan, John Khoury, Allan MacIsaac, Tami Martin, Monica Nitsche, Aaron Peterson, Lamia Raffo, Norton Starr, Jim Trefzger, Aaron Watson, and Weihua Zeng for their suggestions; Joseph Bennish, Craig Chamberlin, Kent Merryfield, and Gina Sanders for insightful conversations on calculus; Al Shenk and Dennis Zill for permission to use exercises from their calculus texts; COMAP for permission to use project material; David Bleecker, Victor Kaftal, Anthony Lam, Jamie Lawson, Ira Rosenholtz, Paul Sally, Lowell Smylie, Larry Wallen, and Jonathan Watson for ideas for exercises; Dan Drucker for the roller derby project; Thomas Banchoff, Tom Farmer, Fred Gass, John Ramsay, Larry Riddle, Philip Straffin, and Klaus Volpert for ideas for projects; Josh Babbin, Scott Barnett, and Gina Sanders for solving the new exercises and suggesting ways to improve them; Jeff Cole for overseeing all the solutions to the exercises and ensuring their correctness; Mary Johnson and Marv Riedesel for accuracy in proofreading, and Doug Shaw for accuracy checking. In addition, we thank Dan Anderson, Ed Barbeau, Fred Brauer, Andy BulmanFleming, Bob Burton, David Cusick, Tom DiCiccio, Garret Etgen, Chris Fisher, Barbara Frank, Leon Gerber, Stuart Goldenberg, Arnold Good, Gene Hecht, Harvey Keynes, E. L. Koh, Zdislav Kovarik, Kevin Kreider, Emile LeBlanc, David Leep, Gerald Leibowitz, Larry Peterson, Mary Pugh, Carl Riehm, John Ringland, Peter Rosenthal, Dusty Sabo, Dan Silver, Simon Smith, Alan Weinstein, and Gail Wolkowicz. We are grateful to Phyllis Panman for assisting us in preparing the manuscript, solving the exercises and suggesting new ones, and for critically proofreading the entire manuscript. We are deeply indebted to our friend and colleague Lothar Redlin who began working with us on this revision shortly before his untimely death in 2018. Lothar’s deep insights into mathematics and its pedagogy, and his lightning fast problemsolving skills, were invaluable assets. We especially thank Kathi Townes of TECHarts, our production service and copyeditor (for this as well as the past several editions). Her extraordinary ability to recall any detail of the manuscript as needed, her facility in simultaneously handling different editing tasks, and her comprehensive familiarity with the book were key factors in its accuracy and timely production. We also thank Lori Heckelman for the elegant and precise rendering of the new illustrations. At Cengage Learning we thank Timothy Bailey, Teni Baroian, Diane Beasley, Carly Belcher, Vernon Boes, Laura Gallus, Stacy Green, Justin Karr, Mark Linton, Samantha Lugtu, Ashley Maynard, Irene Morris, Lynh Pham, Jennifer Risden, Tim Rogers, Mark Santee, Angela Sheehan, and Tom Ziolkowski. They have all done an outstanding job. This textbook has benefited greatly over the past three decades from the advice and guidance of some of the best mathematics editors: Ron Munro, Harry Campbell, Craig Barth, Jeremy Hayhurst, Gary Ostedt, Bob Pirtle, Richard Stratton, Liz Covello, Neha Taleja, and now Gary Whalen. They have all contributed significantly to the success of this book. Prominently, Gary Whalen’s broad knowledge of current issues in the teaching of mathematics and his continual research into creating better ways of using technology as a teaching and learning tool were invaluable resources in the creation of this edition. JA M E S S T E WA RT DA N I E L C L E G G S A L E E M WAT S O N
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A Tribute to James Stewart
james stewart had a singular gift for teaching mathematics. The large lecture halls where he taught his calculus classes were always packed to capacity with students, whom he held engaged with interest and anticipation as he led them to discover a new concept or the solution to a stimulating problem. Stewart presented calculus the way he viewed it — as a rich subject with intuitive concepts, wonderful problems, powerful applications, and a fascinating history. As a testament to his success in teaching and lecturing, many of his students went on to become mathematicians, scientists, and engineers — and more than a few are now university professors themselves. It was his students who first suggested that he write a calculus textbook of his own. Over the years, former students, by then working scientists and engineers, would call him to discuss mathematical problems that they encountered in their work; some of these discussions resulted in new exercises or projects in the book. We each met James Stewart—or Jim as he liked us to call him—through his teaching and lecturing, resulting in his inviting us to coauthor mathematics textbooks with him. In the years we have known him, he was in turn our teacher, mentor, and friend. Jim had several special talents whose combination perhaps uniquely qualified him to write such a beautiful calculus textbook — a textbook with a narrative that speaks to students and that combines the fundamentals of calculus with conceptual insights on how to think about them. Jim always listened carefully to his students in order to find out precisely where they may have had difficulty with a concept. Crucially, Jim really enjoyed hard work — a necessary trait for completing the immense task of writing a calculus book. As his coauthors, we enjoyed his contagious enthusiasm and optimism, making the time we spent with him always fun and productive, never stressful. Most would agree that writing a calculus textbook is a major enough feat for one lifetime, but amazingly, Jim had many other interests and accomplishments: he played violin professionally in the Hamilton and McMaster Philharmonic Orchestras for many years, he had an enduring passion for architecture, he was a patron of the arts and cared deeply about many social and humanitarian causes. He was also a world traveler, an eclectic art collector, and even a gourmet cook. James Stewart was an extraordinary person, mathematician, and teacher. It has been our honor and privilege to be his coauthors and friends. DA N I E L C L E G G S A L E E M WAT S O N
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About the Authors For more than two decades, Daniel Clegg and Saleem Watson have worked with James Stewart on writing mathematics textbooks. The close working relationship between them was particularly productive because they shared a common viewpoint on teaching mathematics and on writing mathematics. In a 2014 interview James Stewart remarked on their collaborations: “We discovered that we could think in the same way . . . we agreed on almost everything, which is kind of rare.” Daniel Clegg and Saleem Watson met James Stewart in different ways, yet in each case their initial encounter turned out to be the beginning of a long association. Stewart spotted Daniel’s talent for teaching during a chance meeting at a mathematics conference and asked him to review the manuscript for an upcoming edition of Calculus and to author the multivariable solutions manual. Since that time Daniel has played an everincreasing role in the making of several editions of the Stewart calculus books. He and Stewart have also coauthored an applied calculus textbook. Stewart first met Saleem when Saleem was a student in his graduate mathematics class. Later Stewart spent a sabbatical leave doing research with Saleem at Penn State University, where Saleem was an instructor at the time. Stewart asked Saleem and Lothar Redlin (also a student of Stewart’s) to join him in writing a series of precalculus textbooks; their many years of collaboration resulted in several editions of these books. james stewart was professor of mathematics at McMaster University and the University of Toronto for many years. James did graduate studies at Stanford University and the University of Toronto, and subsequently did research at the University of London. His research field was Harmonic Analysis and he also studied the connections between mathematics and music. daniel clegg is professor of mathematics at Palomar College in Southern California. He did undergraduate studies at California State University, Fullerton and graduate studies at the University of California, Los Angeles (UCLA). Daniel is a consummate teacher; he has been teaching mathematics ever since he was a graduate student at UCLA. saleem watson is professor emeritus of mathematics at California State University, Long Beach. He did undergraduate studies at Andrews University in Michigan and graduate studies at Dalhousie University and McMaster University. After completing a research fellowship at the University of Warsaw, he taught for several years at Penn State before joining the mathematics department at California State University, Long Beach. Stewart and Clegg have published Brief Applied Calculus. Stewart, Redlin, and Watson have published Precalculus: Mathematics for Calculus, College Algebra, Trigonometry, Algebra and Trigonometry, and (with Phyllis Panman) College Algebra: Concepts and Contexts.
xxiii Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Technology in the Ninth Edition Graphing and computing devices are valuable tools for learning and exploring calculus, and some have become well established in calculus instruction. Graphing calculators are useful for drawing graphs and performing some numerical calculations, like approximating solutions to equations or numerically evaluating derivatives (Chapter 3) or definite integrals (Chapter 5). Mathematical software packages called computer algebra systems (CAS, for short) are more powerful tools. Despite the name, algebra represents only a small subset of the capabilities of a CAS. In particular, a CAS can do mathematics symbolically rather than just numerically. It can find exact solutions to equations and exact formulas for derivatives and integrals. We now have access to a wider variety of tools of varying capabilities than ever before. These include Webbased resources (some of which are free of charge) and apps for smartphones and tablets. Many of these resources include at least some CAS functionality, so some exercises that may have typically required a CAS can now be completed using these alternate tools. In this edition, rather than refer to a specific type of device (a graphing calculator, for instance) or software package (such as a CAS), we indicate the type of capability that is needed to work an exercise.
;
Graphing Icon The appearance of this icon beside an exercise indicates that you are expected to use a machine or software to help you draw the graph. In many cases, a graphing calculator will suffice. Websites such as Desmos.com provide similar capability. If the graph is in 3D (see Chapters 12 – 16), WolframAlpha.com is a good resource. There are also many graphing software applications for computers, smartphones, and tablets. If an exercise asks for a graph but no graphing icon is shown, then you are expected to draw the graph by hand. In Chapter 1 we review graphs of basic functions and discuss how to use transformations to graph modified versions of these basic functions.
Technology Icon This icon is used to indicate that software or a device with abilities beyond just graphing is needed to complete the exercise. Many graphing calculators and software resources can provide numerical approximations when needed. For working with mathematics symbolically, websites like WolframAlpha.com or Symbolab.com are helpful, as are more advanced graphing calculators such as the Texas Instrument TI89 or TINspire CAS. If the full power of a CAS is needed, this will be stated in the exercise, and access to software packages such as Mathematica, Maple, MATLAB, or SageMath may be required. If an exercise does not include a technology icon, then you are expected to evaluate limits, derivatives, and integrals, or solve equations by hand, arriving at exact answers. No technology is needed for these exercises beyond perhaps a basic scientific calculator.
xxiv Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
To the Student Reading a calculus textbook is different from reading a story or a news article. Don’t be discouraged if you have to read a passage more than once in order to understand it. You should have pencil and paper and calculator at hand to sketch a diagram or make a calculation. Some students start by trying their homework problems and read the text only if they get stuck on an exercise. We suggest that a far better plan is to read and understand a section of the text before attempting the exercises. In particular, you should look at the definitions to see the exact meanings of the terms. And before you read each example, we suggest that you cover up the solution and try solving the problem yourself. Part of the aim of this course is to train you to think logically. Learn to write the solutions of the exercises in a connected, stepbystep fashion with explanatory sentences — not just a string of disconnected equations or formulas. The answers to the oddnumbered exercises appear at the back of the book, in Appendix H. Some exercises ask for a verbal explanation or interpretation or description. In such cases there is no single correct way of expressing the answer, so don’t worry that you haven’t found the definitive answer. In addition, there are often several different forms in which to express a numerical or algebraic answer, so if your answer differs from the given one, don’t immediately assume you’re wrong. For example, if the answer given in the back of the book is s2 2 1 and you obtain 1y(1 1 s2 ), then you’re correct and rationalizing the denominator will show that the answers are equivalent. The icon ; indicates an exercise that definitely requires the use of either a graphing calculator or a computer with graphing software to help you sketch the graph. But that doesn’t mean that graphing devices can’t be used to check your work on the other exercises as well. The symbol indicates that technological assistance beyond just graphing is needed to complete the exercise. (See Technology in the Ninth Edition for more details.) You will also encounter the symbol , which warns you against committing an error. This symbol is placed in the margin in situations where many students tend to make the same mistake. Homework Hints are available for many exercises. These hints can be found on StewartCalculus.com as well as in WebAssign. The homework hints ask you questions that allow you to make progress toward a solution without actually giving you the answer. If a particular hint doesn’t enable you to solve the problem, you can click to reveal the next hint. We recommend that you keep this book for reference purposes after you finish the course. Because you will likely forget some of the specific details of calculus, the book will serve as a useful reminder when you need to use calculus in subsequent courses. And, because this book contains more material than can be covered in any one course, it can also serve as a valuable resource for a working scientist or engineer. Calculus is an exciting subject, justly considered to be one of the greatest achievements of the human intellect. We hope you will discover that it is not only useful but also intrinsically beautiful.
xxv Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Diagnostic Tests Success in calculus depends to a large extent on knowledge of the mathematics that precedes calculus: algebra, analytic geometry, functions, and trigonometry. The following tests are intended to diagnose weaknesses that you might have in these areas. After taking each test you can check your answers against the given answers and, if necessary, refresh your skills by referring to the review materials that are provided.
A Diagnostic Test: Algebra 1. Evaluate each expression without using a calculator. (a) s23d4 (b) 234 (c) 324
SD
22
5 23 2 (d) (e) (f) 16 23y4 5 21 3 2. Simplify each expression. Write your answer without negative exponents.
(a) s200 2 s32
s3a 3b 3 ds4ab 2 d 2 (b)
S
D
22
3x 3y2 y 3 (c) x 2 y21y2 3. Expand and simplify. sx 1 3ds4x 2 5d (a) 3sx 1 6d 1 4s2x 2 5d (b) (c) (sa 1 sb )(sa 2 sb ) (d) s2x 1 3d2 (e) sx 1 2d3 4. Factor each expression. (a) 4x 2 2 25 (b) 2x 2 1 5x 2 12 (c) x 3 2 3x 2 2 4x 1 12 (d) x 4 1 27x x 3 y 2 4xy (e) 3x 3y2 2 9x 1y2 1 6x 21y2 (f) 5. S implify the rational expression. (a)
x 2 1 3x 1 2 2x 2 2 x 2 1 x13 (b) x2 2 x 2 2 x2 2 9 2x 1 1
y x 2 x x11 x y (c) 2 2 (d) x 24 x12 1 1 2 y x 2
xxvi Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
DIAGNOSTIC TESTS
xxvii
6. Rationalize the expression and simplify. s10 s4 1 h 2 2 (a) (b) h s5 2 2 7. Rewrite by completing the square. (a) x 2 1 x 1 1 (b) 2x 2 2 12x 1 11 8. Solve the equation. (Find only the real solutions.) 2x 2x 2 1 (a) x 1 5 − 14 2 12 x (b) − x11 x (c) x 2 2 x 2 12 − 0 (d) 2x 2 1 4x 1 1 − 0


(e) x 4 2 3x 2 1 2 − 0 (f) 3 x 2 4 − 10 (g) 2xs4 2 xd21y2 2 3 s4 2 x − 0
9. Solve each inequality. Write your answer using interval notation. (a) 24 , 5 2 3x < 17 (b) x 2 , 2x 1 8 (c) xsx 2 1dsx 1 2d . 0 (d) x24 ,3 2x 2 3 (e) x2 2 1 (e) x 2 1 y 2 , 4 (f) 9x 2 1 16y 2 − 144
ANSWERS TO DIAGNOSTIC TEST B: ANALYTIC GEOMETRY 1. (a) y − 23x 1 1 (b) y − 25 (c) x − 2 (d) y − 12 x 2 6
5. (a)
2. sx 1 1d2 1 s y 2 4d2 − 52
(b)
y 3
2
0
3. Center s3, 25d, radius 5
x
_1
4. (a) 234 (b) 4x 1 3y 1 16 − 0; xintercept 24, yintercept 2 16 3 (c) s21, 24d (d) 20 (e) 3x 2 4y − 13 (f) sx 1 1d2 1 s y 1 4d2 − 100
(d)
_4
1
0
(e)
4x
0
1
x
(f)
y 2
0
y 1
y=1 2 x 2
x
_2
y
_1
(c)
y
0
y=≈1
≈+¥=4 2
x
y
3
0
4 x
If you had difficulty with these problems, you may wish to consult the review of analytic geometry in Appendixes B and C.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
xxix
DIAGNOSTIC TESTS
C Diagnostic Test: Functions y 1. The graph of a function f is given at the left. (a) State the value of f s21d. (b) Estimate the value of f s2d. (c) For what values of x is f sxd − 2? 1 (d) Estimate the values of x such that f sxd − 0. 0 x 1 (e) State the domain and range of f .
2. If f sxd − x 3, evaluate the difference quotient
f s2 1 hd 2 f s2d and simplify your answer. h
3. Find the domain of the function. FIGURE FOR PROBLEM 1
3 x 2x 1 1 s (a) f sxd − 2 (b) (c) hsxd − s4 2 x 1 sx 2 2 1 tsxd − 2 x 1x22 x 11
4. How are graphs of the functions obtained from the graph of f ? (a) y − 2f sxd (b) y − 2 f sxd 2 1 (c) y − f sx 2 3d 1 2 5. Without using a calculator, make a rough sketch of the graph. (a) y − x 3 (b) y − sx 1 1d3 (c) y − sx 2 2d3 1 3 2 y − sx (f) y − 2 sx (d) y − 4 2 x (e) x 21 (g) y − 22 (h) y−11x
H
1 2 x 2 if x < 0 6. Let f sxd − 2x 1 1 if x . 0
(a) Evaluate f s22d and f s1d.
(b) Sketch the graph of f .
7. If f sxd − x 2 1 2x 2 1 and tsxd − 2x 2 3, find each of the following functions. (a) f 8 t (b) t 8 f (c) t8t8t
ANSWERS TO DIAGNOSTIC TEST C: FUNCTIONS 1. (a) 22 (b) 2.8 (c) 23, 1 (d) 22.5, 0.3 (e) f23, 3g, f22, 3g
5. (a)
0
4. (a) Reflect about the xaxis (b) Stretch vertically by a factor of 2, then shift 1 unit downward (c) Shift 3 units to the right and 2 units upward
(d)
(g)
1
x
_1
(2, 3)
2
0
_1
(e)
(h)
x
0
(f)
y
0
x
y
0
y
1
y 4
0
(c)
y
1
2. 12 1 6h 1 h 2 3. (a) s2`, 22d ø s22, 1d ø s1, `d (b) s2`, `d (c) s2`, 21g ø f1, 4g
(b)
y
1
x
1
x
x
y
0
1
y 1
1
x
0
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
x
xxx
DIAGNOSTIC TESTS
6. (a) 23, 3 (b)
7. (a) s f 8 tdsxd − 4x 2 2 8x 1 2
y
(b) s t 8 f dsxd − 2x 2 1 4x 2 5
1 _1
0
x
(c) s t 8 t 8 tdsxd − 8x 2 21
If you had difficulty with these problems, you should look at sections 1.1–1.3 of this book.
D Diagnostic Test: Trigonometry 1. Convert from degrees to radians. (a) 3008 (b) 2188 2. Convert from radians to degrees. (a) 5y6 (b) 2 3. Find the length of an arc of a circle with radius 12 cm if the arc subtends a central angle of 308. 4. Find the exact values. (a) tansy3d (b) sins7y6d (c) secs5y3d
5. Express the lengths a and b in the figure in terms of . 24 a 6. If sin x − 13 and sec y − 54, where x and y lie between 0 and y2, evaluate sinsx 1 yd. ¨ 7. Prove the identities. b 2 tan x (a) tan sin 1 cos − sec (b) 2 − sin 2x 1 1 tan x FIGURE FOR PROBLEM 5
8. Find all values of x such that sin 2x − sin x and 0 < x < 2. 9. Sketch the graph of the function y − 1 1 sin 2x without using a calculator.
ANSWERS TO DIAGNOSTIC TEST D: TRIGONOMETRY 1. (a) 5y3 (b) 2y10 2. (a) 1508 (b) 3608y < 114.68 3. 2 cm 4. (a)
1 6. 15 (4 1 6 s2 )
8. 0, y3, , 5y3, 2 y
9.
221 (c) 2 s3 (b)
2
5. a − 24 sin , b − 24 cos _π
0
π
x
If you had difficulty with these problems, you should look at Appendix D of this book.
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By the time you finish this ourse, you will be able to determine where a pilot should start descent for a smooth landing, find the length of the cu ve used to design the Gateway Arch in St. Louis, compute the force on a baseball bat when it strikes the ball, predict the population sizes for competing predatorprey species, show that bees form the cells of a beehive in a way that uses the least amount of wax, and estimate the amount of fuel needed to propel a rocket into orbit. Top row: Who is Danny / Shutterstock.com; iStock.com / gnagel; Richard Paul Kane / Shutterstock.com Bottom row: Bruce Ellis / Shutterstock.com; Kostiantyn Kravchenko / Shutterstock.com; Ben Cooper / Science Faction / Getty Images
A Preview of Calculus CALCULUS IS FUNDAMENTALLY DIFFERENT from the mathematics that you have studied previously: calculus is less static and more dynamic. It is concerned with change and motion; it deals with quantities that approach other quantities. For that reason it may be useful to have an overview of calculus before beginning your study of the subject. Here we give a preview of some of the main ideas of calculus and show how their foundations are built upon the concept of a limit.
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2
A PREVIEW OF CALCULUS
What Is Calculus? The world around us is continually changing — populations increase, a cup of coffee cools, a stone falls, chemicals react with one another, currency values fluctuate, and so on. We would like to be able to analyze quantities or processes that are undergoing continuous change. For example, if a stone falls 10 feet each second we could easily tell how fast it is falling at any time, but this is not what happens — the stone falls faster and faster, its speed changing at each instant. In studying calculus, we will learn how to model (or describe) such instantaneously changing processes and how to find the cumulative effect of these changes. Calculus builds on what you have learned in algebra and analytic geometry but advances these ideas spectacularly. Its uses extend to nearly every field of human activity. You will encounter numerous applications of calculus throughout this book. At its core, calculus revolves around two key problems involving the graphs of functions — the area problem and the tangent problem — and an unexpected relationship between them. Solving these problems is useful because the area under the graph of a function and the tangent to the graph of a function have many important interpretations in a variety of contexts.
The Area Problem
A¡ A∞
A™
The origins of calculus go back at least 2500 years to the ancient Greeks, who found areas using the “method of exhaustion.” They knew how to find the area A of any polygon by dividing it into triangles, as in Figure 1, and adding the areas of these triangles. It is a much more difficult problem to find the area of a curved figure. The Greek method of exhaustion was to inscribe polygons in the figure and circumscribe polygons about the figure, and then let the number of sides of the polygons increase. Figure 2 illustrates this process for the special case of a circle with inscribed regular polygons.
A¢
A£
A=A¡+A™+A£+A¢+A∞
FIGURE 1
A£
A¢
A∞
Aß
A¶
A¡™
FIGURE 2
Let An be the area of the inscribed regular polygon of n sides. As n increases, it appears that An gets closer and closer to the area of the circle. We say that the area A of the circle is the limit of the areas of the inscribed polygons, and we write y
A − lim An n l`
y=ƒ
A x
0
FIGURE 3 The area A of the region under the graph of f
The Greeks themselves did not use limits explicitly. However, by indirect reasoning, Eudoxus (fifth century bc) used exhaustion to prove the familiar formula for the area of a circle: A − r 2. We will use a similar idea in Chapter 5 to find areas of regions of the type shown in Figure 3. We approximate such an area by areas of rectangles as shown in Figure 4. If we approximate the area A of the region under the graph of f by using n rectangles R1 , R2 , . . . , Rn , then the approximate area is An − R1 1 R2 1 c 1 Rn
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A PREVIEW OF CALCULUS
y
y
R¡
R™
R£
3
y
R¢ x
0
x
0
x
0
FIGURE 4 Approximating the area A using rectangles
Now imagine that we increase the number of rectangles (as the width of each one decreases) and calculate A as the limit of these sums of areas of rectangles: A − lim An n l`
In Chapter 5 we will learn how to calculate such limits. The area problem is the central problem in the branch of calculus called integral calculus; it is important because the area under the graph of a function has different interpretations depending on what the function represents. In fact, the techniques that we develop for finding areas will also enable us to compute the volume of a solid, the length of a curve, the force of water against a dam, the mass and center of mass of a rod, the work done in pumping water out of a tank, and the amount of fuel needed to send a rocket into orbit. y
The Tangent Problem
L y=ƒ P
0
x
FIGURE 5 The tangent line at P y
Consider the problem of trying to find an equation of the tangent line L to a curve with equation y − f sxd at a given point P. (We will give a precise definition of a tangent line in Chapter 2; for now you can think of it as the line that touches the curve at P and follows the direction of the curve at P, as in Figure 5.) Because the point P lies on the tangent line, we can find the equation of L if we know its slope m. The problem is that we need two points to compute the slope and we know only one point, P, on L. To get around the problem we first find an approximation to m by taking a nearby point Q on the curve and computing the slope m PQ of the secant line PQ. Now imagine that Q moves along the curve toward P as in Figure 6. You can see that the secant line PQ rotates and approaches the tangent line L as its limiting position. This y
L
L
Q
Q
Q
P
P
0
y
L
x
0
P x
0
x
FIGURE 6 The secant lines approach the tangent line as Q approaches P.
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4
A PREVIEW OF CALCULUS
y
means that the slope m PQ of the secant line becomes closer and closer to the slope m of the tangent line. We write
L Q { x, ƒ} ƒf(a)
P { a, f(a)}
m − lim mPQ QlP
and say that m is the limit of m PQ as Q approaches P along the curve. Notice from Figure 7 that if P is the point sa, f sadd and Q is the point sx, f sxdd, then
xa
a
0
FIGURE 7 The secant line PQ
x
x
mPQ −
f sxd 2 f sad x2a
Because x approaches a as Q approaches P, an equivalent expression for the slope of the tangent line is m − lim
xla
f sxd 2 f sad x2a
In Chapter 3 we will learn rules for calculating such limits. The tangent problem has given rise to the branch of calculus called differential calculus; it is important because the slope of a tangent to the graph of a function can have different interpretations depending on the context. For instance, solving the tangent problem allows us to find the instantaneous speed of a falling stone, the rate of change of a chemical reaction, or the direction of the forces on a hanging chain.
A Relationship between the Area and Tangent Problems The area and tangent problems seem to be very different problems but, surprisingly, the problems are closely related — in fact, they are so closely related that solving one of them leads to a solution of the other. The relationship between these two problems is introduced in Chapter 5; it is the central discovery in calculus and is appropriately named the Fundamental Theorem of Calculus. Perhaps most importantly, the Fundamental Theorem vastly simplifies the solution of the area problem, making it possible to find areas without having to approximate by rectangles and evaluate the associated limits. Isaac Newton (1642 –1727) and Gottfried Leibniz (1646 –1716) are credited with the invention of calculus because they were the first to recognize the importance of the Fundamental Theorem of Calculus and to utilize it as a tool for solving realworld problems. In studying calculus you will discover these powerful results for yourself.
Summary We have seen that the concept of a limit arises in finding the area of a region and in finding the slope of a tangent line to a curve. It is this basic idea of a limit that sets calculus apart from other areas of mathematics. In fact, we could define calculus as the part of mathematics that deals with limits. We have mentioned that areas under curves and slopes of tangent lines to curves have many different interpretations in a variety of contexts. Finally, we have discussed that the area and tangent problems are closely related. After Isaac Newton invented his version of calculus, he used it to explain the motion of the planets around the sun, giving a definitive answer to a centurieslong quest for a description of our solar system. Today calculus is applied in a great variety of contexts, such as determining the orbits of satellites and spacecraft, predicting population sizes,
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A PREVIEW OF CALCULUS
5
forecasting weather, measuring cardiac output, and gauging the efficiency of an economic market. In order to convey a sense of the power and versatility of calculus, we conclude with a list of some of the questions that you will be able to answer using calculus. 1. How can we design a roller coaster for a safe and smooth ride? (See the Applied Project following Section 3.1.)
2. How far away from an airport should a pilot start descent? (See the Applied Project following Section 3.4.)
3. How can we explain the fact that the angle of elevation from an observer up to the highest point in a rainbow is always 42°? (See the Applied Project following Section 4.1.)
4. How can we estimate the amount of work that was required to build the Great Pyramid of Khufu in ancient Egypt? (See Exercise 36 in Section 6.4.)
5. With what speed must a projectile be launched with so that it escapes the earth’s gravitation pull? (See Exercise 77 in Section 7.8.)
6. How can we explain the changes in the thickness of sea ice over time and why cracks in the ice tend to “heal”? (See Exercise 56 in Section 9.3.)
7. Does a ball thrown upward take longer to reach its maximum height or to fall back down to its original height? (See the Applied Project following Section 9.5.)
8. How can we fit curves together to design shapes to represent letters on a laser printer? (See the Applied Project following Section 10.2.)
9. How can we explain the fact that planets and satellites move in elliptical orbits? (See the Applied Project following Section 13.4.)
10. How can we distribute water flow among turbines at a hydroelectric station so as to maximize the total energy production? (See the Applied Project following Section 14.8.)
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The electrical power produced by a wind turbine can be estimated by a mathematical function that incorporates several factors. We will explore this function in Exercise 1.2.25 and determine the expected power output of a particular turbine for various wind speeds. chaiviewfinder / Shutterstock.com
1
Functions and Models THE FUNDAMENTAL OBJECTS THAT WE deal with in calculus are functions. This chapter prepares the way for calculus by discussing the basic ideas concerning functions, their graphs, and ways of transforming and combining them. We stress that a function can be represented in different ways: by an equation, in a table, by a graph, or in words. We look at the main types of functions that occur in calculus and describe the process of using these functions as mathematical models of realworld phenomena.
7 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
8
CHAPTER 1 Functions and Models
1.1 Four Ways to Represent a Function ■ Functions Functions arise whenever one quantity depends on another. Consider the following four situations. A. The area A of a circle depends on the radius r of the circle. The rule that connects r and A is given by the equation A − r 2. With each positive number r there is associated one value of A, and we say that A is a function of r. Table 1 World Population Year
Population (millions)
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
1650 1750 1860 2070 2300 2560 3040 3710 4450 5280 6080 6870
B. The human population of the world P depends on the time t. Table 1 gives estimates of the world population P at time t, for certain years. For instance, P < 2,560,000,000
when t − 1950
For each value of the time t there is a corresponding value of P, and we say that P is a function of t. C. The cost C of mailing an envelope depends on its weight w. Although there is no simple formula that connects w and C, the post office has a rule for determining C when w is known. D. The vertical acceleration a of the ground as measured by a seismograph during an earthquake is a function of the elapsed time t. Figure 1 shows a graph generated by seismic activity during the Northridge earthquake that shook Los Angeles in 1994. For a given value of t, the graph provides a corresponding value of a. a
{cm/[email protected]}
100 50
5
FIGURE 1 Vertical ground acceleration during the Northridge earthquake
10
15
20
25
30
t (seconds)
_50 Calif. Dept. of Mines and Geology
Each of these examples describes a rule whereby, given a number (r in Example A), another number (A) is assigned. In each case we say that the second number is a function of the first number. If f represents the rule that connects A to r in Example A, then we express this in function notation as A − f srd. A function f is a rule that assigns to each element x in a set D exactly one element, called f sxd, in a set E. We usually consider functions for which the sets D and E are sets of real numbers. The set D is called the domain of the function. The number f sxd is the value of f at x and is read “ f of x.” The range of f is the set of all possible values of f sxd as x varies
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9
SECTION 1.1 Four Ways to Represent a Function
x (input)
ƒ (output)
f
FIGURE 2
Machine diagram for a function f
x
ƒ a
f(a)
f
D
throughout the domain. A symbol that represents an arbitrary number in the domain of a function f is called an independent variable. A symbol that represents a number in the range of f is called a dependent variable. In Example A, for instance, r is the independent variable and A is the dependent variable. It’s helpful to think of a function as a machine (see Figure 2). If x is in the domain of the function f, then when x enters the machine, it’s accepted as an input and the machine produces an output f sxd according to the rule of the function. So we can think of the domain as the set of all possible inputs and the range as the set of all possible outputs. The preprogrammed functions in a calculator are good examples of a function as a machine. For example, if you input a number and press the squaring key, the calculator displays the output, the square of the input. Another way to picture a function is by an arrow diagram as in Figure 3. Each arrow connects an element of D to an element of E. The arrow indicates that f sxd is associated with x, f sad is associated with a, and so on. Perhaps the most useful method for visualizing a function is its graph. If f is a function with domain D, then its graph is the set of ordered pairs

hsx, f sxdd x [ Dj
E
(Notice that these are inputoutput pairs.) In other words, the graph of f consists of all points sx, yd in the coordinate plane such that y − f sxd and x is in the domain of f. The graph of a function f gives us a useful picture of the behavior or “life history” of a function. Since the ycoordinate of any point sx, yd on the graph is y − f sxd, we can read the value of f sxd from the graph as being the height of the graph above the point x. (See Figure 4.) The graph of f also allows us to picture the domain of f on the xaxis and its range on the yaxis as in Figure 5.
FIGURE 3
Arrow diagram for f
y y
f (1)f (1) 0 0
y y
{ x, ƒ { x, ƒ } }
1 1
f (2)f (2)
2 2
ƒƒ
x x
x x
FIGURE 4
range range
0 0
ƒ(x) y y ƒ(x)
domain domain
x x
FIGURE 5
y
EXAMPLE 1 The graph of a function f is shown in Figure 6. (a) Find the values of f s1d and f s5d. (b) What are the domain and range of f ?
1
SOLUTION (a) We see from Figure 6 that the point s1, 3d lies on the graph of f, so the value of f at 1 is f s1d − 3. (In other words, the point on the graph that lies above x − 1 is 3 units above the xaxis.) When x − 5, the graph lies about 0.7 units below the xaxis, so we estimate that f s5d < 20.7. (b) We see that f sxd is defined when 0 < x < 7, so the domain of f is the closed interval f0, 7g. Notice that f takes on all values from 22 to 4, so the range of f is
0
1
x
FIGURE 6 The notation for intervals is given in Appendix A.

hy 22 < y < 4j − f22, 4g
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■
10
CHAPTER 1 Functions and Models
In calculus, the most common method of defining a function is by an algebraic equation. For example, the equation y − 2x 2 1 defines y as a function of x. We can express this in function notation as fsxd − 2x 2 1. y
EXAMPLE 2 Sketch the graph and find the domain and range of each function. (a) fsxd − 2x 2 1 (b) tsxd − x 2 y=2x1
0 1
x
1 2
FIGURE 7 y
(2, 4)
y=≈ (_1, 1)

1 0
1
SOLUTION (a) The equation of the graph is y − 2x 2 1, and we recognize this as being the equation of a line with slope 2 and yintercept 21. (Recall the slopeintercept form of the equation of a line: y − mx 1 b. See Appendix B.) This enables us to sketch a portion of the graph of f in Figure 7. The expression 2x 2 1 is defined for all real numbers, so the domain of f is the set of all real numbers, which we denote by R. The graph shows that the range is also R. (b) Since ts2d − 2 2 − 4 and ts21d − s21d2 − 1, we could plot the points s2, 4d and s21, 1d, together with a few other points on the graph, and join them to produce the graph (Figure 8). The equation of the graph is y − x 2, which represents a parabola (see Appendix C). The domain of t is R. The range of t consists of all values of tsxd, that is, all numbers of the form x 2. But x 2 > 0 for all numbers x and any positive number y is a square. So the range of t is hy y > 0j − f0, `d. This can also be seen from Figure 8.
x
■
f sa 1 hd 2 f sad EXAMPLE 3 If f sxd − 2x 2 2 5x 1 1 and h ± 0, evaluate . h SOLUTION We first evaluate f sa 1 hd by replacing x by a 1 h in the expression for f sxd:
FIGURE 8
f sa 1 hd − 2sa 1 hd2 2 5sa 1 hd 1 1 − 2sa 2 1 2ah 1 h 2 d 2 5sa 1 hd 1 1 − 2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1
The expression
Then we substitute into the given expression and simplify: f sa 1 hd 2 f sad s2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1d 2 s2a 2 2 5a 1 1d − h h
f sa 1 hd 2 f sad h in Example 3 is called a difference quotient and occurs frequently in calculus. As we will see in Chapter 2, it represents the average rate of change of f sxd between x − a and x − a 1 h.
2a 2 1 4ah 1 2h 2 2 5a 2 5h 1 1 2 2a 2 1 5a 2 1 h 2 4ah 1 2h 2 5h − − 4a 1 2h 2 5 h −
■
■ Representations of Functions We consider four different ways to represent a function: ●
verbally
(by a description in words)
●
numerically
(by a table of values)
●
visually
(by a graph)
●
algebraically
(by an explicit formula)
If a single function can be represented in all four ways, it’s often useful to go from one representation to another to gain additional insight into the function. (In Example 2, for instance, we started with algebraic formulas and then obtained graphs.) But certain functions are described more naturally by one method than by another. With this in mind, let’s reexamine the four situations that we considered at the beginning of this section. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
11
SECTION 1.1 Four Ways to Represent a Function
Table 2 World Population t (years since 1900)
Population (millions)
0 10 20 30 40 50 60 70 80 90 100 110
1650 1750 1860 2070 2300 2560 3040 3710 4450 5280 6080 6870
A. The most useful representation of the area of a circle as a function of its radius is probably the algebraic formula A − r 2 or, in function notation, Asrd − r 2. It is also possible to compile a table of values or sketch a graph (half a parabola). Because a circle has to have a positive radius, the domain is hr r . 0j − s0, `d and the range is also s0, `d. B. We are given a description of the function in words: Pstd is the human population of the world at time t. Let’s measure t so that t − 0 corresponds to the year 1900. Table 2 provides a convenient representation of this function. If we plot the ordered pairs in the table, we get the graph (called a scatter plot) in Figure 9. It too is a useful representation; the graph allows us to absorb all the data at once. What about a formula? Of course, it’s impossible to devise an explicit formula that gives the exact human population Pstd at any time t. But it is possible to find an expression for a function that approximates Pstd. In fact, using methods explained in Section 1.4, we obtain an approximation for the population P:

Pstd < f std − s1.43653 3 10 9 d ∙ s1.01395d t Figure 10 shows that it is a reasonably good “fit.” The function f is called a mathematical model for population growth. In other words, it is a function with an explicit formula that approximates the behavior of our given function. We will see, however, that the ideas of calculus can be applied to a table of values; an explicit formula is not necessary.
P
P
5x10'
5x10'
0
20
40
60 80 Years since 1900
FIGURE 9
100
120
t
0
20
40
60 80 Years since 1900
100
120
t
FIGURE 10
A function deﬁned by a table of values is called a tabular function.
Table 3 w (grams)
Cswd (dollars)
0 , w , 25
1.00
25 , w , 50 50 , w , 75 75 , w , 100 100 , w , 125 ∙ ∙ ∙
1.15 1.30 1.45 1.60 ∙ ∙ ∙
The function P is typical of the functions that arise whenever we attempt to apply calculus to the real world. We start with a verbal description of a function. Then we may be able to construct a table of values of the function, perhaps from instrument readings in a scientific experiment. Even though we don’t have complete knowledge of the values of the function, we will see throughout the book that it is still possible to perform the operations of calculus on such a function. C. Again, the function is described in words: Let Cswd be the cost of mailing a large envelope with weight w. The rule that the US Postal Service used as of 2019 is as follows: The cost is 1 dollar for up to 25 g plus 15 cents for each additional gram (or less) up to 350 g. A table of values is the most convenient representation for this function (see Table 3), though it is possible to sketch a graph (see Example 10). D. The graph shown in Figure 1 is the most natural representation of the vertical acceleration function astd. It’s true that a table of values could be compiled, and it is even possible to devise an approximate formula. But everything a geologist needs to
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12
CHAPTER 1 Functions and Models
know— amplitudes and patterns — can be seen easily from the graph. (The same is true for the patterns seen in electrocardiograms of heart patients and polygraphs for liedetection.) In the next example we sketch the graph of a function that is defined verbally.
EXAMPLE 4 When you turn on a hotwater faucet that is connected to a hotwater tank, the temperature T of the water depends on how long the water has been running. Draw a rough graph of T as a function of the time t that has elapsed since the faucet was turned on.
T
t
0
FIGURE 11
SOLUTION The initial temperature of the running water is close to room temperature because the water has been sitting in the pipes. When the water from the hotwater tank starts flowing from the faucet, T increases quickly. In the next phase, T is constant at the temperature of the heated water in the tank. When the tank is drained, T decreases to the temperature of the water supply. This enables us to make the rough sketch of T as a function of t shown in Figure 11. ■ In the following example we start with a verbal description of a function in a physical situation and obtain an explicit algebraic formula. The ability to do this is a useful skill in solving calculus problems that ask for the maximum or minimum values of quantities.
EXAMPLE 5 A rectangular storage container with an open top has a volume of 10 m3. The length of its base is twice its width. Material for the base costs $10 per square meter; material for the sides costs $6 per square meter. Express the cost of materials as a function of the width of the base.
h w 2w
FIGURE 12
SOLUTION We draw a diagram as in Figure 12 and introduce notation by letting w and 2w be the width and length of the base, respectively, and h be the height. The area of the base is s2wdw − 2w 2, so the cost, in dollars, of the material for the base is 10s2w 2 d. Two of the sides have area wh and the other two have area 2wh, so the cost of the material for the sides is 6f2swhd 1 2s2whdg. The total cost is therefore C − 10s2w 2 d 1 6f2swhd 1 2s2whdg − 20 w 2 1 36 wh To express C as a function of w alone, we need to eliminate h and we do so by using the fact that the volume is 10 m3. Thus w s2wdh − 10
which gives PS In setting up applied functions as in
Example 5, it may be useful to review the principles of problem solving at the end of this chapter, particularly Step 1: Understand the Problem.
h−
10 5 − 2 2w 2 w
Substituting this into the expression for C, we have
S D
C − 20w 2 1 36w
5
w
2
− 20w 2 1
180 w
Therefore the equation Cswd − 20w 2 1 expresses C as a function of w.
180 w
w . 0 ■
In the next example we find the domain of a function that is defined algebraically. If a function is given by a formula and the domain is not stated explicitly, we use the Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.1 Four Ways to Represent a Function
13
following domain convention: the domain of the function is the set of all inputs for which the formula makes sense and gives a realnumber output.
EXAMPLE 6 Find the domain of each function. (a) f sxd − sx 1 2 (b) tsxd −
1 x 2x 2
SOLUTION (a) Because the square root of a negative number is not defined (as a real number), the domain of f consists of all values of x such that x 1 2 > 0. This is equivalent to x > 22, so the domain is the interval f22, `d. (b) Since 1 1 tsxd − 2 − x 2x xsx 2 1d and division by 0 is not allowed, we see that tsxd is not defined when x − 0 or x − 1. So the domain of t is hx x ± 0, x ± 1j

which could also be written in interval notation as s2`, 0d ø s0, 1d ø s1, `d
■
■ Which Rules Define Functions?
y
0
x=a
Not every equation defines a function. The equation y − x 2 defines y as a function of x because the equation determines exactly one value of y for each value of x. However, the equation y 2 − x does not define y as a function of x because some input values x correspond to more than one output y; for instance, for the input x − 4 the equation gives the outputs y − 2 and y − 2. Similarly, not every table defines a function. Table 3 defined C as a function of w — each package weight w corresponds to exactly one mailing cost. On the other hand, Table 4 does not define y as a function of x because some input values x in the table correspond to more than one output y; for instance, the input x − 5 gives the outputs y − 7 and y − 8.
(a, b)
Table 4
x
a
(a) This curve represents a function. y (a, c)
x=a
a
(b) This curve doesn’t represent a function.
FIGURE 13
2
4
5
5
6
y
3
6
7
8
9
What about curves drawn in the xyplane? Which curves are graphs of functions? The following test gives an answer. The Vertical Line Test A curve in the xyplane is the graph of a function of x if and only if no vertical line intersects the curve more than once.
(a, b) 0
x
x
The reason for the truth of the Vertical Line Test can be seen in Figure 13. If each vertical line x − a intersects a curve only once, at sa, bd, then exactly one function value is defined by f sad − b. But if a line x − a intersects the curve twice, at sa, bd and sa, cd, then the curve can’t represent a function because a function can’t assign two different values to a.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
14
CHAPTER 1 Functions and Models
For example, the parabola x − y 2 2 2 shown in Figure 14(a) is not the graph of a function of x because, as you can see, there are vertical lines that intersect the parabola twice. The parabola, however, does contain the graphs of two functions of x. Notice that the equation x − y 2 2 2 implies y 2 − x 1 2, so y − 6sx 1 2 . Thus the upper and lower halves of the parabola are the graphs of the functions f sxd − s x 1 2 [from Example 6(a)] and tsxd − 2s x 1 2 . [See Figures 14(b) and (c).] y
(_2, 0)
FIGURE 14
0
y
x
_2 0
y _2
x
(b) y=œ„„„„ x+2
(a) x=¥2
0
x
(c) y=_ œ„„„„ x+2
We observe that if we reverse the roles of x and y, then the equation x − hsyd − y 2 2 2 does define x as a function of y (with y as the independent variable and x as the dependent variable). The graph of the function h is the parabola in Figure 14(a).
■ Piecewise Deﬁned Functions The functions in the following four examples are defined by different formulas in dif ferent parts of their domains. Such functions are called piecewise defined functions.
EXAMPLE 7 A function f is defined by f sxd −
H
1 2 x if x < 21 x2 if x . 21
Evaluate f s22d, f s21d, and f s0d and sketch the graph. SOLUTION Remember that a function is a rule. For this particular function the rule is the following: First look at the value of the input x. If it happens that x < 21, then the value of f sxd is 1 2 x. On the other hand, if x . 21, then the value of f sxd is x 2. Note that even though two different formulas are used, f is one function, not two. Since 22 < 21, we have f s22d − 1 2 s22d − 3. Since 21 < 21, we have f s21d − 1 2 s21d − 2.
y
Since 0 . 21, we have f s0d − 0 2 − 0.
1
_1
0
1
x
FIGURE 15
How do we draw the graph of f ? We observe that if x < 21, then f sxd − 1 2 x, so the part of the graph of f that lies to the left of the vertical line x − 21 must coincide with the line y − 1 2 x, which has slope 21 and yintercept 1. If x . 21, then f sxd − x 2, so the part of the graph of f that lies to the right of the line x − 21 must coincide with the graph of y − x 2, which is a parabola. This enables us to sketch the graph in Figure 15. The solid dot indicates that the point s21, 2d is included on the graph; the open dot indicates that the point s21, 1d is excluded from the graph. ■ The next example of a piecewise defined function is the absolute value function. Recall that the absolute value of a number a, denoted by a , is the distance from a to 0 on the real number line. Distances are always positive or 0, so we have
 
For a more extensive review of absolute values, see Appendix A.
 a  > 0 for every number a
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.1 Four Ways to Represent a Function
15
For example,
 3  − 3  23  − 3  0  − 0  s2 2 1  − s2 2 1  3 2  − 2 3 In general, we have
 a  − a if  a  − 2a if
a>0 a,0
(Remember that if a is negative, then 2a is positive.)
EXAMPLE 8 Sketch the graph of the absolute value function f sxd −  x .
y
y= x 
SOLUTION From the preceding discussion we know that
x − 0
x
H
x if x > 0 2x if x , 0
Using the same method as in Example 7, we see that the graph of f coincides with the line y − x to the right of the yaxis and coincides with the line y − 2x to the left of the yaxis (see Figure 16). ■
FIGURE 16 y
EXAMPLE 9 Find a formula for the function f graphed in Figure 17.
1
SOLUTION The line through s0, 0d and s1, 1d has slope m − 1 and yintercept b − 0, so its equation is y − x. Thus, for the part of the graph of f that joins s0, 0d to s1, 1d, we have f sxd − x if 0 < x < 1
0
x
1
The line through s1, 1d and s2, 0d has slope m − 21, so its pointslope form is
FIGURE 17
y 2 0 − s21dsx 2 2d or y − 2 2 x
The pointslope form of the equation of a line is y 2 y1 − msx 2 x 1 d . See Appendix B.
So we have
f sxd − 2 2 x if 1 , x < 2
We also see that the graph of f coincides with the xaxis for x . 2. Putting this information together, we have the following threepiece formula for f :
H
x if 0 < x < 1 f sxd − 2 2 x if 1 , x < 2 0 if x . 2 C 1.50
EXAMPLE 10 In Example C at the beginning of this section we considered the cost Cswd of mailing a large envelope with weight w. In effect, this is a piecewise defined function because, from Table 3, we have
1.00 0.50
0
■
Cswd − 25
FIGURE 18
50
75
100
125 w
1.00 1.15 1.30 1.45 ∙ ∙ ∙
if if if if
0 , w , 25 25 , w , 50 50 , w , 75 75 , w , 100
The graph is shown in Figure 18.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
■
16
CHAPTER 1 Functions and Models
Looking at Figure 18, you can see why a function like the one in Example 10 is called a step function.
■ Even and Odd Functions
y
f(_x)
If a function f satisfies f s2xd − f sxd for every number x in its domain, then f is called an even function. For instance, the function f sxd − x 2 is even because
ƒ _x
0
x
x
f s2xd − s2xd2 − x 2 − f sxd The geometric significance of an even function is that its graph is symmetric with respect to the yaxis (see Figure 19). This means that if we have plotted the graph of f for x > 0, we obtain the entire graph simply by reflecting this portion about the yaxis. If f satisfies f s2xd − 2f sxd for every number x in its domain, then f is called an odd function. For example, the function f sxd − x 3 is odd because
FIGURE 19 An even function y _x
0
f s2xd − s2xd3 − 2x 3 − 2f sxd ƒ x
x
The graph of an odd function is symmetric about the origin (see Figure 20). If we already have the graph of f for x > 0, we can obtain the entire graph by rotating this portion through 1808 about the origin.
EXAMPLE 11 Determine whether each of the following functions is even, odd, or neither even nor odd. (a) f sxd − x 5 1 x (b) tsxd − 1 2 x 4 (c) hsxd − 2x 2 x 2
FIGURE 20
SOLUTION (a)
An odd function
f s2xd − s2xd5 1 s2xd − s21d5x 5 1 s2xd − 2x 5 2 x − 2sx 5 1 xd − 2f sxd
Therefore f is an odd function. ts2xd − 1 2 s2xd4 − 1 2 x 4 − tsxd
(b) So t is even.
hs2xd − 2s2xd 2 s2xd2 − 22x 2 x 2
(c)
Since hs2xd ± hsxd and hs2xd ± 2hsxd, we conclude that h is neither even nor odd. ■ The graphs of the functions in Example 11 are shown in Figure 21. Notice that the graph of h is symmetric neither about the yaxis nor about the origin. 1
_1
y
y
y
1
f
1
g 1
x
h
1
x
1
x
_1
FIGURE 21
(a)
( b)
(c)
■ Increasing and Decreasing Functions The graph shown in Figure 22 rises from A to B, falls from B to C, and rises again from C to D. The function f is said to be increasing on the interval fa, bg, decreasing on fb, cg, and increasing again on fc, dg. Notice that if x 1 and x 2 are any two numbers between Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 1.1 Four Ways to Represent a Function
17
a and b with x 1 , x 2, then f sx 1 d , f sx 2 d. We use this as the defining property of an increasing function. B
y
D
y=ƒ
f(x¡)
A 0
FIGURE 22
a x¡
C
f(x™)
x™
b
c
d
x
A function f is called increasing on an interval I if f sx 1 d , f sx 2 d whenever x 1 , x 2 in I
y
y=≈
It is called decreasing on I if f sx 1 d . f sx 2 d whenever x 1 , x 2 in I In the definition of an increasing function it is important to realize that the inequality f sx 1 d , f sx 2 d must be satisfied for every pair of numbers x 1 and x 2 in I with x 1 , x 2. You can see from Figure 23 that the function f sxd − x 2 is decreasing on the interval s2`, 0g and increasing on the interval f0, `d.
x
0
FIGURE 23
1.1 Exercises 1. If f sxd − x 1 s2 2 x and tsud − u 1 s2 2 u , is it true that f − t ? 2. If
4. The graphs of f and t are given.
x2 2 x and tsxd − x f sxd − x21
is it true that f − t ? 3. The graph of a function t is given. (a) State the values of ts2d, ts0d, ts2d, and ts3d. (b) For what value(s) of x is tsxd − 3 ? (c) For what value(s) of x is tsxd ⩽ 3 ? (d) State the domain and range of t. (e) On what interval(s) is t increasing? y 3
_3
0
g
3
(a) State the values of f s24d and ts3d. (b) Which is larger, f s23d or ts3d ?
(c) For what values of x is f sxd − tsxd ?
(d) On what interval(s) is f sxd ⩽ tsxd ?
(e) State the solution of the equation f sxd − 21.
(f ) On what interval(s) is t decreasing?
(g) State the domain and range of f.
(h) State the domain and range of t. y
f
g 2 0
2
x
x
5. Figure 1 was recorded by an instrument operated by the California Department of Mines and Geology at the Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
18
CHAPTER 1 Functions and Models
University Hospital of the University of Southern California in Los Angeles. Use it to estimate the range of the vertical ground acceleration function at USC during the Northridge earthquake.
(c) The years when the temperature was smallest and largest (d) The range of T T (•C)
6. In this section we discussed examples of ordinary, everyday functions: population is a function of time, postage cost is a function of package weight, water temperature is a function of time. Give three other examples of functions from everyday life that are described verbally. What can you say about the domain and range of each of your functions? If possible, sketch a rough graph of each function.
14
13
7–14 Determine whether the equation or table defines y as a function of x.
9. x 1 sy 2 3d − 5
10. 2xy 1 5y − 4
11. s y 1 3d3 1 1 − 2x
12. 2x 2 y − 0
13.
14.
2
2
2
 
x y Height (cm) Shoe size 180 150 150 160 175
12 8 7 9 10
x y Year Tuition cost ($)
2016 2017 2018 2019 2020
10,900 11,000 11,200 11,200 11,300
15–18 Determine whether the curve is the graph of a function of x. If it is, state the domain and range of the function. 15.
17.
yy y
16.
yy y
11 1
11 1
00 0 11 1 xx x
00 0 11 1 xx x
yy y
yy y
18.
11 1
11 1
00 0 11 1 xx x
0 0 11 1 x x
19. Shown is a graph of the global average temperature T during the 20th century. Estimate the following. (a) The global average temperature in 1950 (b) The year when the average temperature was 14.2°C
2000 t
1950
Source: Adapted from Globe and Mail [Toronto], 5 Dec. 2009. Print.
20. Trees grow faster and form wider rings in warm years and grow more slowly and form narrower rings in cooler years. The figure shows ring widths of a Siberian pine from 1500 to 2000. (a) What is the range of the ring width function? (b) What does the graph tend to say about the temperature of the earth? Does the graph reflect the volcanic eruptions of the mid19th century? R
Ring width (mm)
8. 3x 2 2 2y − 5
7. 3x 2 5y − 7
1900
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
1500
1600
1700
1800
1900
2000 t
Year Source: Adapted from G. Jacoby et al., “Mongolian Tree Rings and 20thCentury Warming,” Science 273 (1996): 771–73.
21. You put some ice cubes in a glass, fill the glass with cold water, and then let the glass sit on a table. Describe how the temperature of the water changes as time passes. Then sketch a rough graph of the temperature of the water as a function of the elapsed time. 22. You place a frozen pie in an oven and bake it for an hour. Then you take it out and let it cool. Describe how the temperature of the pie changes as time passes. Then sketch a rough graph of the temperature of the pie as a function of time. 23. The graph shows the power consumption for a day in September in San Francisco. (P is measured in megawatts; t is mea sured in hours starting at midnight.) (a) What was the power consumption at 6 am? At 6 pm?
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19
SECTION 1.1 Four Ways to Represent a Function
(b) When was the power consumption the lowest? When was it the highest? Do these times seem reasonable? P 800
31. T emperature readings T (in °C) were recorded every two hours from midnight to 2:00 pm in Atlanta on a day in June. The time t was measured in hours from midnight.
600 400
200 0
3
6
9
12
15
18
21
t
Pacific Gas & Electric
24. Three runners compete in a 100meter race. The graph depicts the distance run as a function of time for each runner. Describe in words what the graph tells you about this race. Who won the race? Did each runner finish the race? y 100
0
A
B
C
20
25. Sketch a rough graph of the outdoor temperature as a function of time during a typical spring day. 26. Sketch a rough graph of the number of hours of daylight as a function of the time of year. 27. Sketch a rough graph of the amount of a particular brand of coffee sold by a store as a function of the price of the coffee. 28. Sketch a rough graph of the market value of a new car as a function of time for a period of 20 years. Assume the car is well maintained. 29. A homeowner mows the lawn every Wednesday afternoon. Sketch a rough graph of the height of the grass as a function of time over the course of a fourweek period. 30. An airplane takes off from an airport and lands an hour later at another airport, 650 kilometers away. If t represents the time in minutes since the plane has left the terminal building, let xstd be the horizontal distance traveled and ystd be the altitude of the plane. (a) Sketch a possible graph of xstd. (b) Sketch a possible graph of ystd. (c) Sketch a possible graph of the ground speed. (d) Sketch a possible graph of the vertical velocity.
t
0
2
4
6
8
10
12
14
T
23
21
20
19
21
26
28
30
(a) Use the readings to sketch a rough graph of T as a function of t. (b) Use your graph to estimate the temperature at 9:00 am.
32. Researchers measured the blood alcohol concentration (BAC) of eight adult male subjects after rapid consumption of 30 mL of ethanol (corresponding to two standard alcoholic drinks). The table shows the data they obtained by averaging the BAC (in gydL) of the eight men. (a) Use the readings to sketch a graph of the BAC as a function of t. (b) Use your graph to describe how the effect of alcohol varies with time. t (hours)
BAC
t (hours)
BAC
0 0.2 0.5 0.75 1.0 1.25 1.5
0 0.025 0.041 0.040 0.033 0.029 0.024
1.75 2.0 2.25 2.5 3.0 3.5 4.0
0.022 0.018 0.015 0.012 0.007 0.003 0.001
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after Oral Administration in the Fasting State,” Journal of Pharmacokinetics and Biopharmaceutics 5 (1977): 207–24.
33. If f sxd − 3x 2 2 x 1 2, find f s2d, f s22d, f sad, f s2ad, f sa 1 1d, 2 f sad, f s2ad, f sa 2 d, [ f sad] 2, and f sa 1 hd. x , find ts0d, ts3d, 5tsad, 12 ts4ad, tsa 2 d, sx 1 1 ftsad 2, tsa 1 hd, and tsx 2 ad.
34. If tsxd −
35–38 Evaluate the difference quotient for the given function. Simplify your answer. f s3 1 hd 2 f s3d 35. f sxd − 4 1 3x 2 x 2, h 36. f sxd − x 3, 37. f sxd −
f sa 1 hd 2 f sad h
1 f sxd 2 f sad , x x2a
38. f sxd − sx 1 2,
f sxd 2 f s1d x21
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20
CHAPTER 1 Functions and Models
39–46 Find the domain of the function. 39. f sxd −
x14 x2 2 9
40. f sxd −
1 sx 2 2 5x 4
44. f sud −
u11 1 11 u11 2
47. Find the domain and range and sketch the graph of the function hsxd − s4 2 x 2 . 48. Find the domain and sketch the graph of the function x2 2 4 x22
f sxd −
50. f sxd − 51. f sxd − 52. f sxd −
H H H H
x 2 1 2 if x , 0 x if x > 0 5 if x , 2 1 x 2 3 if x>2 2


H  x 1
56.
   
x
65. A rectangle has perimeter 20 m. Express the area of the rectangle as a function of the length of one of its sides. 66. A rectangle has area 16 m2. Express the perimeter of the rect angle as a function of the length of one of its sides. 67. Express the area of an equilateral triangle as a function of the length of a side.
69. An open rectangular box with volume 2 m3 has a square base. Express the surface area of the box as a function of the length of a side of the base.
30
 x f sxd −

x
if x < 1 if x . 1
 x  2 1
1
50
54. f sxd − x 1 2
55. tstd − 1 2 3t
0
65–70 Find a formula for the described function and state its domain.
21 if x < 1 7 2 2x if x . 1
 
x
1
71. A box with an open top is to be constructed from a rectan gular piece of cardboard with dimensions 30 cm by 50 cm by cutting out equal squares of side x at each corner and then folding up the sides as in the figure. Express the volume V of the box as a function of x.
x 1 1 if x < 21 x2 if x . 21
53. f sxd − x 1 x
58. tsxd −
0
1
70. A right circular cylinder has volume 400 cm3. Express the radius of the cylinder as a function of the height.
53–58 Sketch the graph of the function.
57. f sxd −
1
68. A closed rectangular box with volume 0.25 m3 has length twice the width. Express the height of the box as a function of the width.
49–52 Evaluate f s23d, f s0d, and f s2d for the piecewise defined function. Then sketch the graph of the function. 49. f sxd −
y
x2 1 1 x 1 4x 2 21
46. hsxd − sx 2 4x 2 5
45. Fs pd − s2 2 s p
64.
2
42. tstd − s3 2 t 2 s2 1 t
3 41. f std − s 2t 2 1
43. hsxd −
y
63.
x x
x
x
x
x
x x
72. A Norman window has the shape of a rectangle surmounted by a semicircle. If the perimeter of the window is 10 m, express the area A of the window as a function of the width x of the window.
59–64 Find a formula for the function whose graph is the given curve. 59. The line segment joining the points s1, 23d and s5, 7d 60. The line segment joining the points s25, 10d and s7, 210d 61. The bottom half of the parabola x 1 s y 2 1d 2 − 0 62. The top half of the circle x 2 1 s y 2 2d 2 − 4
x
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SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
73. In a certain state the maximum speed permitted on freeways is 100 kmyh and the minimum speed is 60 kmyh. The fine for violating these limits is $15 for every kilometer per hour above the maximum speed or below the minimum speed. Express the amount of the fine F as a function of the driving speed x and graph Fsxd for 0 < x < 150.
79–80 The graph of a function defined for x > 0 is given. Complete the graph for x , 0 to make (a) an even function and (b) an odd function. y
79.
74. An electricity company charges its customers a base rate of $10 a month, plus 6 cents per kilowatthour (kWh) for the first 1200 kWh and 7 cents per kWh for all usage over 1200 kWh. Express the monthly cost E as a function of the amount x of electricity used. Then graph the function E for 0 < x < 2000. 75. In a certain country, income tax is assessed as follows. There is no tax on income up to $10,000. Any income over $10,000 is taxed at a rate of 10%, up to an income of $20,000. Any income over $20,000 is taxed at 15%. (a) Sketch the graph of the tax rate R as a function of the income I. (b) How much tax is assessed on an income of $14,000? On $26,000? (c) Sketch the graph of the total assessed tax T as a function of the income I. 76. (a) If the point s5, 3d is on the graph of an even function, what other point must also be on the graph? (b) If the point s5, 3d is on the graph of an odd function, what other point must also be on the graph? 77–78 Graphs of f and t are shown. Decide whether each function is even, odd, or neither. Explain your reasoning. 77.
y
g
78.
y
21
0
80.
x
y
0
x
81–86 Determine whether f is even, odd, or neither. You may wish to use a graphing calculator or computer to check your answer visually. x2 x 11
81. f sxd −
x x 11
82. f sxd −
83. f sxd −
x x11
84. f sxd − x x
2
85. f sxd − 1 1 3x 2 2 x 4
4
 
86. f sxd − 1 1 3x 3 2 x 5
f
f x
g
x
87. If f and t are both even functions, is f 1 t even? If f and t are both odd functions, is f 1 t odd? What if f is even and t is odd? Justify your answers. 88. If f and t are both even functions, is the product ft even? If f and t are both odd functions, is ft odd? What if f is even and t is odd? Justify your answers.
1.2 Mathematical Models: A Catalog of Essential Functions A mathematical model is a mathematical description (often by means of a function or an equation) of a realworld phenomenon such as the size of a population, the demand for a product, the speed of a falling object, the concentration of a product in a chemical reaction, the life expectancy of a person at birth, or the cost of emissions reductions. The purpose of the model is to understand the phenomenon and perhaps to make predictions about future behavior. Given a realworld problem, our first task in the mathematical modeling process is to formulate a mathematical model by identifying and naming the independent and dependent variables and making assumptions that simplify the phenomenon enough to make it mathematically tractable. We use our knowledge of the physical situation and our
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22
CHAPTER 1 Functions and Models
mathematical skills to obtain equations that relate the variables. In situations where there is no physical law to guide us, we may need to collect data (either from the Internet or a library or by conducting our own experiments) and examine the data in the form of a table in order to discern patterns. From this numerical representation of a function we may wish to obtain a graphical representation by plotting the data. The graph might even suggest a suitable algebraic formula in some cases. The second stage is to apply the mathematics that we know (such as the calculus that will be developed throughout this book) to the mathematical model that we have formulated in order to derive mathematical conclusions. Then, in the third stage, we take those mathematical conclusions and interpret them as information about the original realworld phenomenon by way of offering explanations or making predictions. The final step is to test our predictions by checking against new real data. If the predictions don’t compare well with reality, we need to refine our model or formulate a new model and start the cycle again. Figure 1 illustrates the process of mathematical modeling. Realworld problem
Formulate
Mathematical model
Mathematical conclusions
Solve
Interpret
Realworld predictions
Test
FIGURE 1
A mathematical model is never a completely accurate representation of a physical situation—it is an idealization. A good model simplifies reality enough to permit mathematical calculations but is accurate enough to provide valuable conclusions. It is important to realize the limitations of a model. There are many different types of functions that can be used to model relationships observed in the real world. In what follows, we discuss the behavior and graphs of some of these functions and give examples of situations appropriately modeled by such functions.
The modeling process
■ Linear Models The coordinate geometry of lines is reviewed in Appendix B.
When we say that y is a linear function of x, we mean that the graph of the function is a line, so we can use the slopeintercept form of the equation of a line to write a formula for the function as y − f sxd − mx 1 b where m is the slope of the line and b is the yintercept. A characteristic feature of linear functions is that they change at a constant rate. For instance, Figure 2 shows a graph of the linear function f sxd − 3x 2 2 and a table of sample values. Notice that whenever x increases by 0.1, the value of f sxd increases by 0.3. So f sxd increases three times as fast as x. This means that the slope of the graph of y − 3x 2 2, namely 3, can be interpreted as the rate of change of y with respect to x. y
y=3x2
0 _2
FIGURE 2
1
x
x
f sxd − 3x 2 2
1.0 1.1 1.2 1.3 1.4 1.5
1.0 1.3 1.6 1.9 2.2 2.5
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SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
23
EXAMPLE 1 (a) As dry air moves upward, it expands and cools. If the ground temperature is 20°C and the temperature at a height of 1 km is 10°C, express the temperature T (in °C) as a function of the height h (in kilometers), assuming that a linear model is appropriate. (b) Draw the graph of the function in part (a). What does the slope represent? (c) What is the temperature at a height of 2.5 km? SOLUTION (a) Because we are assuming that T is a linear function of h, we can write T − mh 1 b We are given that T − 20 when h − 0, so 20 − m ? 0 1 b − b In other words, the yintercept is b − 20. We are also given that T − 10 when h − 1, so
T 20 10
10 − m ? 1 1 20 T=_10h+20
The slope of the line is therefore m − 10 2 20 − 210 and the required linear function is T − 210h 1 20
0
1
h
3
FIGURE 3
( b) The graph is sketched in Figure 3. The slope is m − 210°Cykm, and this represents the rate of change of temperature with respect to height. (c) At a height of h − 2.5 km, the temperature is
T − 210s2.5d 1 20 − 25°C
■
If there is no physical law or principle to help us formulate a model, we construct an empirical model, which is based entirely on collected data. We seek a curve that “fits” the data in the sense that it captures the basic trend of the data points. Table 1 Year
CO2 level (in ppm)
Year
CO2 level (in ppm)
1980 1984 1988 1992 1996
338.7 344.4 351.5 356.3 362.4
2000 2004 2008 2012 2016
369.4 377.5 385.6 393.8 404.2
EXAMPLE 2 Table 1 lists the average carbon dioxide level in the atmosphere, measured in parts per million at Mauna Loa Observatory from 1980 to 2016. Use the data in Table 1 to find a model for the carbon dioxide level. SOLUTION We use the data in Table 1 to make the scatter plot in Figure 4, where t represents time (in years) and C represents the CO2 level (in parts per million, ppm). C (ppm) 410 400 390 380 370 360 350 340
FIGURE 4 Scatter plot for the average CO2 level
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
t
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24
CHAPTER 1 Functions and Models
Notice that the data points appear to lie close to a straight line, so it’s natural to choose a linear model in this case. But there are many possible lines that approximate these data points, so which one should we use? One possibility is the line that passes through the first and last data points. The slope of this line is 404.2 2 338.7 65.5 − < 1.819 2016 2 1980 36 We write its equation as C 2 338.7 − 1.819st 2 1980d or 1 A computer or graphing calculator ﬁnds the regression line by the method of least squares, which is to minimize the sum of the squares of the vertical distances between the data points and the line. The details are explained in Exercise 14.7.61.
C − 1.819t 2 3262.92
Equation 1 gives one possible linear model for the carbon dioxide level; it is graphed in Figure 5. Notice that our model gives values higher than most of the actual CO2 levels. A better linear model is obtained by a procedure from statistics called linear regression. Many graphing calculators and computer software applications can determine the regression line for a set of data. One such calculator gives the slope and yintercept of the regression line for the data from Table 1 as m − 1.78242 b − 23192.90 So our least squares model for the CO2 level is 2
C − 1.78242t 2 3192.90
In Figure 6 we graph the regression line as well as the data points. Comparing with Figure 5, we see that the regression line gives a better fit.
C (ppm)
C (ppm)
410
410
400
400
390
390
380
380
370
370
360
360
350
350
340
340 1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
t
1980 1984 1988 1992 1996 2000 2004 2008 2012 2016
FIGURE 5
FIGURE 6
Linear model through first and last data points
The regression line
t
■
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SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
25
EXAMPLE 3 Use the linear model given by Equation 2 to estimate the average CO2 level for 1987 and to predict the level for the year 2025. According to this model, when will the CO2 level exceed 440 parts per million? SOLUTION Using Equation 2 with t − 1987, we estimate that the average CO2 level in 1987 was Cs1987d − 1.78242s1987d 2 3192.90 < 348.77 This is an example of interpolation because we have estimated a value between observed values. (In fact, the Mauna Loa Observatory reported that the average CO2 level in 1987 was 348.93 ppm, so our estimate is quite accurate.) With t − 2025, we get Cs2025d − 1.78242s2025d 2 3192.90 < 416.50 So we predict that the average CO2 level in the year 2025 will be 416.5 ppm. This is an example of extrapolation because we have predicted a value outside the time frame of observations. Consequently, we are far less certain about the accuracy of our prediction. Using Equation 2, we see that the CO2 level exceeds 440 ppm when 1.78242t 2 3192.90 . 440 Solving this inequality, we get t.
3632.9 < 2038.18 1.78242
We therefore predict that the CO2 level will exceed 440 ppm by the year 2038. This prediction is risky because it involves a time quite remote from our observations. In fact, we see from Figure 6 that the trend has been for CO2 levels to increase rather more rapidly in recent years, so the level might exceed 440 ppm well before 2038.
y 2
■
■ Polynomials 0
1
x
A function P is called a polynomial if Psxd − a n x n 1 a n21 x n21 1 ∙ ∙ ∙ 1 a 2 x 2 1 a 1 x 1 a 0
(a) y=≈+x+1
where n is a nonnegative integer and the numbers a 0 , a 1, a 2 , . . . , a n are constants called the coefficients of the polynomial. The domain of any polynomial is R − s2`, `d. If the leading coefficient a n ± 0, then the degree of the polynomial is n. For example, the function
y 2
Psxd − 2x 6 2 x 4 1 25 x 3 1 s2 1
x
(b) y=_2≈+3x+1
FIGURE 7 The graphs of quadratic functions are parabolas.
is a polynomial of degree 6. A polynomial of degree 1 is of the form Psxd − mx 1 b and so it is a linear function. A polynomial of degree 2 is of the form Psxd − ax 2 1 bx 1 c and is called a quadratic function. Its graph is always a parabola obtained by shifting the parabola y − ax 2, as we will see in Section 1.3. The parabola opens upward if a . 0 and downward if a , 0. (See Figure 7.) A polynomial of degree 3 is of the form Psxd − ax 3 1 bx 2 1 cx 1 d a ± 0
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26
CHAPTER 1 Functions and Models
and is called a cubic function. Figure 8 shows the graph of a cubic function in part (a) and graphs of polynomials of degrees 4 and 5 in parts (b) and (c). We will see later why the graphs have these shapes. y
y
1
2
0
FIGURE 8
1
y 20
1
x
x
(a) y=˛x+1
x
1
(b) y=x$3≈+x
(c) y=3x%25˛+60x
Polynomials are commonly used to model various quantities that occur in the natural and social sciences. For instance, in Section 3.7 we will explain why economists often use a polynomial Psxd to represent the cost of producing x units of a commodity. In the following example we use a quadratic function to model the fall of a ball. Table 2 Time (seconds)
Height (meters)
0 1 2 3 4 5 6 7 8 9
450 445 431 408 375 332 279 216 143 61
EXAMPLE 4 A ball is dropped from the upper observation deck of the CN Tower, 450 m above the ground, and its height h above the ground is recorded at 1second intervals in Table 2. Find a model to fit the data and use the model to predict the time at which the ball hits the ground. SOLUTION We draw a scatter plot of the data in Figure 9 and observe that a linear model is inappropriate. But it looks as if the data points might lie on a parabola, so we try a quadratic model instead. Using a graphing calculator or computer algebra system (which uses the least squares method), we obtain the following quadratic model: h − 449.36 1 0.96t 2 4.90t 2
3 h (meters)
h
400
400
200
200
0
2
4
6
8
t (seconds)
0
2
4
6
8
FIGURE 9
FIGURE 10
Scatter plot for a falling ball
Quadratic model for a falling ball
t
In Figure 10 we plot the graph of Equation 3 together with the data points and see that the quadratic model gives a very good fit. The ball hits the ground when h − 0, so we solve the quadratic equation 24.90t 2 1 0.96t 1 449.36 − 0
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27
SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
The quadratic formula gives t−
20.96 6 ss0.96d2 2 4s24.90ds449.36d 2s24.90d
The positive root is t < 9.67, so we predict that the ball will hit the ground after falling about 9.7 seconds. ■
■ Power Functions A function of the form f sxd − x a, where a is a constant, is called a power function. We consider several cases. ( i ) a − n, where n is a positive integer
The graphs of f sxd − x n for n − 1, 2, 3, 4, and 5 are shown in Figure 11. (These are polynomials with only one term.) We already know the shape of the graphs of y − x (a line through the origin with slope 1) and y − x 2 [a parabola, see Example 1.1.2(b)]. y
y=x
y=≈
y
y
1
1 0
1
x
0
y=x#
y
x
0
1
x
0
y=x%
y
1
1 1
y=x$
1 1
x
0
x
1
FIGURE 11 Graphs of f sxd − x n for n − 1, 2, 3, 4, 5
The general shape of the graph of f sxd − x n depends on whether n is even or odd. If n is even, then f sxd − x n is an even function and its graph is similar to the parabola y − x 2. If n is odd, then f sxd − x n is an odd function and its graph is similar to that of y − x 3. Notice from Figure 12, however, that as n increases, the graph of y − x n becomes flatter near 0 and steeper when x > 1. (If x is small, then x 2 is smaller, x 3 is even smaller, x 4 is smaller still, and so on.)
 
y
A family of functions is a collection of functions whose equations are related. Figure 12 shows two families of power functions, one with even powers and one with odd powers.
y=x ^ (_1, 1)
FIGURE 12
y
y=x $ y=≈ (1, 1)
0
y=x #
(1, 1) y=x %
0
x
x
(_1, _1)
( ii ) a − 1yn, where n is a positive integer n The function f sxd − x 1yn − s x is a root function. For n − 2 it is the square root function f sxd − sx , whose domain is f0, `d and whose graph is the upper half of the
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28
CHAPTER 1 Functions and Models n parabola x − y 2. [See Figure 13(a).] For other even values of n, the graph of y − s x is 3 similar to that of y − sx . For n − 3 we have the cube root function f sxd − sx whose domain is R (recall that every real number has a cube root) and whose graph is shown n 3 in Figure 13(b). The graph of y − s x for n odd sn . 3d is similar to that of y − s x.
y
y (1, 1) 0
FIGURE 13
(1, 1) x
0
x (a) ƒ=œ„
Graphs of root functions
x
x (b) ƒ=Œ„
( iii ) a 5 21
The graph of the reciprocal function f sxd − x 21 − 1yx is shown in Figure 14. Its graph has the equation y − 1yx, or xy − 1, and is a hyperbola with the coordinate axes as its asymptotes. This function arises in physics and chemistry in connection with Boyle’s Law, which says that when the temperature is constant, the volume V of a gas is inversely proportional to the pressure P: V−
C P
where C is a constant. Thus the graph of V as a function of P (see Figure 15) has the same general shape as the right half of Figure 14. y
V
y=∆ 1 0
V= 1
x
0
C P
P
FIGURE 1 4
FIGURE 1 5
The reciprocal function
Volume as a function of pressure at constant temperature
( iv ) a 5 22
Among the remaining negative powers for the power function f sxd − x a, by far the most important is that of a − 22. Many natural laws state that one quantity is inversely proportional to the square of another quantity. In other words, the first quantity is modeled by a function of the form f sxd − Cyx 2 and we refer to this as an inverse square law. For instance, the illumination I of an object by a light source is inversely proportional to the square of the distance x from the source: I−
C x2
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29
SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
where C is a constant. Thus the graph of I as a function of x (see Figure 17) has the same general shape as the right half of Figure 16. y
I
y=
1 ≈
I=
C ≈
1 0
1
0
x
x
FIGURE 16
FIGURE 17
The reciprocal of the squaring function
Illumination from a light source as a function of distance from the source
Inverse square laws model gravitational force, loudness of sound, and electrostatic force between two charged particles. See Exercise 37 for a geometric reason why inverse square laws often occur in nature. Power functions are also used to model speciesarea relationships (Exercises 35–36) and the period of revolution of a planet as a function of its distance from the sun (see Exercise 34).
■ Rational Functions y
A rational function f is a ratio of two polynomials: f sxd −
20 0
2
x
Psxd Qsxd
where P and Q are polynomials. The domain consists of all values of x such that Qsxd ± 0. A simple example of a rational function is the function f sxd − 1yx, whose domain is hx x ± 0j; this is the reciprocal function graphed in Figure 14. The function

f sxd −
FIGURE 18 f sxd −
2x 4 2 x 2 1 1 x2 2 4
2x 4 2 x 2 1 1 x2 2 4

is a rational function with domain hx x ± 62j. Its graph is shown in Figure 18.
■ Algebraic Functions A function f is called an algebraic function if it can be constructed using algebraic operations (such as addition, subtraction, multiplication, division, and taking roots) starting with polynomials. Any rational function is automatically an algebraic function. Here are two more examples: f sxd − sx 2 1 1 tsxd −
x 4 2 16x 2 x 1 sx
3 1 sx 2 2d s x11
In Chapter 4 we will sketch a variety of algebraic functions, and we will see that their graphs can assume many different shapes.
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30
CHAPTER 1 Functions and Models
An example of an algebraic function occurs in the theory of relativity. The mass of a particle with velocity v is m − f svd −
m0 s1 2 v 2yc 2
where m 0 is the rest mass of the particle and c − 3.0 3 10 5 kmys is the speed of light in a vacuum. Functions that are not algebraic are called transcendental; these include the trigonometric, exponential, and logarithmic functions.
■ Trigonometric Functions Trigonometry and the trigonometric functions are reviewed on Reference Page 2 and also in Appendix D. In calculus the convention is that radian measure is always used (except when otherwise indicated). For example, when we use the function f sxd − sin x, it is understood that sin x means the sine of the angle whose radian measure is x. Thus the graphs of the sine and cosine functions are as shown in Figure 19.
The Reference Pages are located at the front and back of the book.
y _ _π
π 2
y 3π 2
1 _1
0
π 2
π
_π 2π
5π 2
3π
x
_
π 2
1 _1
(a) ƒ=sin x
FIGURE 19
π 0
3π 3π 2
π 2
2π
5π 2
x
(b) ©=cos x
Notice that for both the sine and cosine functions the domain is s2`, `d and the range is the closed interval f21, 1g. Thus, for all values of x, we have
21 < sin x < 1 21 < cos x < 1
or, in terms of absolute values,
 sin x  < 1  cos x  < 1 An important property of the sine and cosine functions is that they are periodic functions and have period 2. This means that, for all values of x,
sinsx 1 2d − sin x cossx 1 2d − cos x
The periodic nature of these functions makes them suitable for modeling repetitive phenomena such as tides, vibrating springs, and sound waves. For instance, in Example 1.3.4 we will see that a reasonable model for the number of hours of daylight in Philadelphia t days after January 1 is given by the function
F
Lstd − 12 1 2.8 sin
2 st 2 80d 365
G
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SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
31
1 . 1 2 2 cos x SOLUTION This function is defined for all values of x except for those that make the denominator 0. But 5 1 1 2n 1 2 2 cos x − 0 &? cos x − &? x − 1 2n or x − 3 2 3
EXAMPLE 5 Find the domain of the function f sxd −
y
where n is any integer (because the cosine function has period 2). So the domain of f is the set of all real numbers except for the ones noted above. ■
1 _
3π 2
0
_π _ π 2
π 2
π
3π 2
x
The tangent function is related to the sine and cosine functions by the equation tan x −
sin x cos x
and its graph is shown in Figure 20. It is undefined whenever cos x − 0, that is, when x − 6y2, 63y2, . . . . Its range is s2`, `d. Notice that the tangent function has period :
FIGURE 20
tansx 1 d − tan x for all x
y − tanxx y=tan
The remaining three trigonometric functions (cosecant, secant, and cotangent) are the reciprocals of the sine, cosine, and tangent functions. Their graphs are shown in Appendix D. y
1 0
■ Exponential Functions
y
1 0
x
1
(a) y=2®
1
x
(b) y=(0.5)®
FIGURE 21
y
■ Logarithmic Functions The logarithmic functions f sxd − log b x, where the base b is a positive constant, are the inverse functions of the exponential functions. They will be studied in Section 1.5. Figure 22 shows the graphs of four logarithmic functions with various bases. In each case the domain is s0, `d, the range is s2`, `d, and the function increases slowly when x . 1.
y=log™ x y=log£ x
1 0
1
FIGURE 22
The exponential functions are the functions of the form f sxd − b x, where the base b is a positive constant. The graphs of y − 2 x and y − s0.5d x are shown in Figure 21. In both cases the domain is s2`, `d and the range is s0, `d. Exponential functions will be studied in detail in Section 1.4, and we will see that they are useful for modeling many natural phenomena, such as when populations grow (if b . 1) or decline (if b , 1d.
x
y=log¡¸ x
y=log∞ x
EXAMPLE 6 Classify the following functions as one of the types of functions that we have discussed. 11x (a) f sxd − 5 x (b) tsxd − x 5 (c) hsxd − (d) ustd − 1 2 t 1 5t 4 1 2 sx SOLUTION (a) f sxd − 5 x is an exponential function. (The variable x is the exponent.) (b) tsxd − x 5 is a power function. (The variable x is the base.) We could also consider it to be a polynomial of degree 5. 11x (c) hsxd − is an algebraic function. (It is not a rational function because the 1 2 sx denominator is not a polynomial.) (d) ustd − 1 2 t 1 5t 4 is a polynomial of degree 4. ■ Table 3 (on the following page) shows a summary of graphs of some families of essential functions that will be used frequently throughout the book.
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32
CHAPTER 1 Functions and Models
Table 3 Families of Essential Functions and Their Graphs Linear Functions
y
y
f sxd − mx 1 b b
b
x
0
ƒ=b
Power Functions
b
x
0
ƒ=mx+b
y
y
y
y
f sxd − x n x
0 x
0
y
ƒ=x$
ƒ=x%
y
y
x
x
0
ƒ=˛
ƒ=≈
Root Functions
0
y
n f sxd − s x
x
0
ƒ= œ„ x
Reciprocal Functions f sxd −
1 xn
0
x
x
1 x
0
0
x
1 ƒ= x$
0
x
1
1 x
0
ƒ=b® (b>1)
Trigonometric Functions
x
y
y
1
y
1 ƒ= ˛
f sxd − b x f sxd − log b x
x
%x ƒ=œ„
0
x
1 ƒ= ≈
y
0
y
y
0
x
$x ƒ=œ„
ƒ=Œ„ x
y
ƒ=
Exponential and Logarithmic Functions
0
0
x
ƒ=b® (b1) y
y 1
f sxd − sin x f sxd − cos x f sxd − tan x
0
ƒ=sin x
π
2π x
0
ƒ=cos x
π
2π
x
_
π 2
0
π 2
x
ƒ=tan x
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33
SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
1.2 Exercises 1–2 Classify each function as a power function, root function, polynomial (state its degree), rational function, algebraic function, trigonometric function, exponential function, or logarithmic function.
5–6 Find the domain of the function. 5. f sxd −
cos x 1 2 sin x
6. tsxd −
1 1 2 tan x
1. (a) f sxd − x 3 1 3x 2 (b) tstd − cos2 t 2 sin t v std − 8 t (c) r std − t s3 (d)
(e) y −
sx x2 1 1
2. (a) f std −
(f ) tsud − log10 u
3t 2 1 2 (b) hsrd − 2.3 r t
(c) sstd − st 1 4 (d) y − x4 1 5 1 (f ) y − 2 x
(e) tsxd − sx 3
3–4 Match each equation with its graph. Explain your choices. (Don’t use a computer or graphing calculator.)
8. What do all members of the family of linear functions f sxd − 1 1 msx 1 3d have in common? Sketch several members of the family. 9. What do all members of the family of linear functions f sxd − c 2 x have in common? Sketch several members of the family. ; 10. Sketch several members of the family of polynomials Psxd − x 3 2 cx 2. How does the graph change when c changes?
3. (a) y − x 2 (b) y − x 5 (c) y − x 8 g
7. (a) Find an equation for the family of linear functions with slope 2 and sketch several members of the family. (b) Find an equation for the family of linear functions such that f s2d − 1. Sketch several members of the family. (c) Which function belongs to both families?
y
h
11–12 Find a formula for the quadratic function whose graph is shown. y 18
11. y 18
0
f
0
4. (a) y − 3x (b) y − 3x (c) y − x (d) y − sx 3
3
y
F g
f x
G
y y (_2, 2) (_2, 2) (0, 1) (0, 1)
f
f
x
12.
30
(4, 2) 3
(4, 2) x
x
g
g
0
0
x
x
(1, _2.5)(1, _2.5)
13. Find a formula for a cubic function f if f s1d − 6 and f s21d − f s0d − f s2d − 0. 14. Recent studies indicate that the average surface temperature of the earth has been rising steadily. Some scientists have modeled the temperature by the linear function T − 0.02t 1 8.50, where T is temperature in °C and t represents years since 1900. (a) What do the slope and Tintercept represent? (b) Use the equation to predict the earth’s average surface temperature in 2100. 15. If the recommended adult dosage for a drug is D (in mg), then to determine the appropriate dosage c for a child of age a, pharmacists use the equation c − 0.0417Dsa 1 1d. Suppose the dosage for an adult is 200 mg. (a) Find the slope of the graph of c. What does it represent? (b) What is the dosage for a newborn?
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
34
CHAPTER 1 Functions and Models
16. The manager of a weekend flea market knows from past experience that if he charges x dollars for a rental space at the market, then the number y of spaces that will be rented is given by the equation y − 200 2 4x. (a) Sketch a graph of this linear function. (Remember that the rental charge per space and the number of spaces rented can’t be negative quantities.) (b) What do the slope, the yintercept, and the xintercept of the graph represent? 17. The relationship between the Fahrenheit sFd and Celsius sCd temperature scales is given by the linear function F − 95 C 1 32. (a) Sketch a graph of this function. (b) What is the slope of the graph and what does it represent? What is the Fintercept and what does it represent? 18. Jade and her roommate Jari commute to work each morning, traveling west on I10. One morning Jade left for work at 6:50 am, but Jari left 10 minutes later. Both drove at a constant speed. The graphs show the distance (in kilometers) each of them has traveled on I10, t minutes after 7:00 am. (a) Use the graph to decide which driver is traveling faster. (b) Find the speed (in kmyh) at which each of them is driving. (c) Find linear functions f and t that model the distances traveled by Jade and Jari as functions of t (in minutes). Distance traveled (km)
y 45 30
(6, 25)
15
(6, 11)
0
3
6
Jade Jari
9
Time since 7:00 AM (min)
12
t
19. The manager of a furniture factory finds that it costs $2200 to manufacture 100 chairs in one day and $4800 to produce 300 chairs in one day. (a) Express the cost as a function of the number of chairs produced, assuming that it is linear. Then sketch the graph. (b) What is the slope of the graph and what does it represent? (c) What is the yintercept of the graph and what does it represent? 20. The monthly cost of driving a car depends on the number of kilometers driven. Lynn found that in May it cost her $380 to drive 770 km and in June it cost her $460 to drive 1290 km. (a) Express the monthly cost C as a function of the distance driven d, assuming that a linear relationship gives a suitable model. (b) Use part (a) to predict the cost of driving 2400 km per month. (c) Draw the graph of the linear function. What does the slope represent? (d) What does the Cintercept represent? (e) Why does a linear function give a suitable model in this situation?
21. At the surface of the ocean, the water pressure is the same as the air pressure above the water, 1.05 kgycm2. Below the surface, the water pressure increases by 0.3 kgycm2 for every 3 m of descent. (a) Express the water pressure as a function of the depth below the ocean surface. (b) At what depth is the pressure 7 kgycm2 ? 22. The resistance R of a wire of fixed length is related to its diameter x by an inverse square law, that is, by a function of the form Rsxd − kx 22. (a) A wire of fixed length and 0.005 meters in diameter has a resistance of 140 ohms. Find the value of k. (b) Find the resistance of a wire made of the same material and of the same length as the wire in part (a) but with a diameter of 0.008 meters. 23. The illumination of an object by a light source is related to the distance from the source by an inverse square law. Suppose that after dark you are sitting in a room with just one lamp, trying to read a book. The light is too dim, so you move your chair halfway to the lamp. How much brighter is the light? 24. The pressure P of a sample of oxygen gas that is compressed at a constant temperature is related to the volume V of gas by a reciprocal function of the form P − kyV. (a) A sample of oxygen gas that occupies 0.671 m3 exerts a pressure of 39 kPa at a temperature of 293 K (absolute temperature measured on the Kelvin scale). Find the value of k in the given model. (b) If the sample expands to a volume of 0.916 m3, find the new pressure. 25. The power output of a wind turbine depends on many factors. It can be shown using physical principles that the power P generated by a wind turbine is modeled by P − kAv 3
where v is the wind speed, A is the area swept out by the blades, and k is a constant that depends on air density, efficiency of the turbine, and the design of the wind turbine blades. (a) If only wind speed is doubled, by what factor is the power output increased? (b) If only the length of the blades is doubled, by what factor is the power output increased? (c) For a particular wind turbine, the length of the blades is 30 m and k − 0.214 kgym3. Find the power output (in watts, W − m2 ? kgys3 ) when the wind speed is 10 mys, 15 mys, and 25 mys.
26. Astronomers infer the radiant exitance (radiant flux emitted per unit area) of stars using the Stefan Boltzmann Law: EsT d − s5.67 3 1028 dT 4 where E is the energy radiated per unit of surface area
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35
SECTION 1.2 Mathematical Models: A Catalog of Essential Functions
measured in watts (W) and T is the absolute temperature measured in kelvins (K). (a) Graph the function E for temperatures T between 100 K and 300 K. (b) Use the graph to describe the change in energy E as the temperature T increases.
30. When laboratory rats are exposed to asbestos fibers, some of them develop lung tumors. The table lists the results of several experiments by different scientists. (a) Find the regression line for the data. (b) Make a scatter plot and graph the regression line. Does the regression line appear to be a suitable model for the data? (c) What does the yintercept of the regression line represent?
27–28 For each scatter plot, decide what type of function you might choose as a model for the data. Explain your choices. 27. ((a) a)
y
(b) (b)
0
x
0
x
Asbestos Percent of mice exposure that develop (fibersymL) lung tumors
0
(b) (b)
28. (a) (a) y
y
50 400 500 900 1100
x
y
0
x
29. The table shows (lifetime) peptic ulcer rates (per 100 population) for various family incomes as reported by the National Health Interview Survey. (a) Make a scatter plot of these data and decide whether a linear model is appropriate. (b) Find and graph a linear model using the first and last data points. (c) Find and graph the regression line. (d) Use the linear model in part (c) to estimate the ulcer rate for people with an income of $25,000. (e) According to the model, how likely is someone with an income of $80,000 to suffer from peptic ulcers? (f ) Do you think it would be reasonable to apply the model to someone with an income of $200,000?
Income
Ulcer rate (per 100 population)
$4,000 $6,000 $8,000 $12,000 $16,000 $20,000 $30,000 $45,000 $60,000
14.1 13.0 13.4 12.5 12.0 12.4 10.5 9.4 8.2
2 6 5 10 26
Asbestos exposure (fibersymL)
Percent of mice that develop lung tumors
1600 1800 2000 3000
42 37 38 50
31. Anthropologists use a linear model that relates human femur (thighbone) length to height. The model allows an anthropologist to determine the height of an individual when only a partial skeleton (including the femur) is found. Here we find the model by analyzing the data on femur length and height for the eight males given in the table. (a) Make a scatter plot of the data. (b) Find and graph the regression line that models the data. (c) An anthropologist finds a human femur of length 53 cm. How tall was the person? Femur length (cm)
Height (cm)
Femur length (cm)
Height (cm)
50.1 48.3 45.2 44.7
178.5 173.6 164.8 163.7
44.5 42.7 39.5 38.0
168.3 165.0 155.4 155.8
32. The table shows average US retail residential prices of electricity from 2000 to 2016, measured in cents per kilowatt hour. (a) Make a scatter plot. Is a linear model appropriate? (b) Find and graph the regression line. (c) Use your linear model from part (b) to estimate the average retail price of electricity in 2005 and 2017. Years since 2000 CentsykWh Years since 2000 CentsykWh 0 2 4 6 8
8.24 8.44 8.95 10.40 11.26
10 12 14 16
11.54 11.88 12.52 12.90
Source: US Energy Information Administration
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36
CHAPTER 1 Functions and Models
33. The table shows world average daily oil consumption from 1985 to 2015, measured in thousands of barrels per day. (a) Make a scatter plot and decide whether a linear model is appropriate. (b) Find and graph the regression line. (c) Use the linear model to estimate the oil consumption in 2002 and 2017. Years since 1985
Thousands of barrels of oil per day
0 5 10 15 20 25 30
60,083 66,533 70,099 76,784 84,077 87,302 94,071
Source: US Energy Information Administration
34. The table shows the mean (average) distances d of the planets from the sun (taking the unit of measurement to be the distance from the earth to the sun) and their periods T (time of revolution in years). (a) Fit a power model to the data. (b) Kepler’s Third Law of Planetary Motion states that “The square of the period of revolution of a planet is proportional to the cube of its mean distance from the sun.” Does your model corroborate Kepler’s Third Law? Planet
d
T
Mercury Venus Earth Mars Jupiter Saturn Uranus Neptune
0.387 0.723 1.000 1.523 5.203 9.541 19.190 30.086
0.241 0.615 1.000 1.881 11.861 29.457 84.008 164.784
35. It makes sense that the larger the area of a region, the larger the number of species that inhabit the region. Many ecologists have modeled the speciesarea relation with a power function. In particular, the number of species S of bats living in caves in central Mexico has been related to the surface area A of the caves by the equation S − 0.7A0.3. (a) The cave called Misión Imposible near Puebla, Mexico, has a surface area of A − 60 m2. How many species of bats would you expect to find in that cave? (b) If you discover that four species of bats live in a cave, estimate the area of the cave. 36. The table shows the number N of species of reptiles and amphibians inhabiting Caribbean islands and the area A of the island in square kilometers. (a) Use a power function to model N as a function of A. (b) The Caribbean island of Dominica has area 753 km 2. How many species of reptiles and amphibians would you expect to find on Dominica? Island Saba Monserrat Puerto Rico Jamaica Hispaniola Cuba
A
N 10
5
103
9
8,959
40
11,424
39
79,192
84
114,524
76
37. Suppose that a force or energy originates from a point source and spreads its influence equally in all directions, such as the light from a lightbulb or the gravitational force of a planet. So at a distance r from the source, the intensity I of the force or energy is equal to the source strength S divided by the surface area of a sphere of radius r. Show that I satisfies the inverse square law I − kyr 2, where k is a positive constant.
1.3 New Functions from Old Functions In this section we start with the basic functions we discussed in Section 1.2 and obtain new functions by shifting, stretching, and reflecting their graphs. We also show how to combine pairs of functions by the standard arithmetic operations and by composition.
■ Transformations of Functions By applying certain transformations to the graph of a given function we can obtain the graphs of related functions. This will give us the ability to sketch the graphs of many functions quickly by hand. It will also enable us to write equations for given graphs.
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37
SECTION 1.3 New Functions from Old Functions
Let’s first consider translations of graphs. If c is a positive number, then the graph of y − f sxd 1 c is just the graph of y − f sxd shifted upward a distance of c units (because each ycoordinate is increased by the same number c). Likewise, if tsxd − f sx 2 cd, where c . 0, then the value of t at x is the same as the value of f at x 2 c (c units to the left of x). Therefore the graph of y − f sx 2 cd is just the graph of y − f sxd shifted c units to the right (see Figure 1). Vertical and Horizontal Shifts Suppose c . 0. To obtain the graph of
y − f sxd 1 c, shift the graph of y − f sxd a distance c units upward y − f sxd 2 c, shift the graph of y − f sxd a distance c units downward y − f sx 2 cd, shift the graph of y − f sxd a distance c units to the right y − f sx 1 cd, shift the graph of y − f sxd a distance c units to the left y
y
y=ƒ+c
y=f(x+c)
c
y =ƒ
c 0
y=cƒ (c>1) y=f(_x)
y=f(xc)
y=ƒ y= 1c ƒ
c x
c
x
0
y=ƒc y=_ƒ
FIGURE 1 Translating the graph of f
FIGURE 2 Stretching and reflecting the graph of f
Now let’s consider the stretching and reflecting transformations. If c . 1, then the graph of y − cf sxd is the graph of y − f sxd stretched by a factor of c in the vertical direction (because each ycoordinate is multiplied by the same number c). The graph of y − 2f sxd is the graph of y − f sxd reflected about the xaxis because the point sx, yd is replaced by the point sx, 2yd. (See Figure 2 and the following chart, where the results of other stretching, shrinking, and reflecting transformations are also given.) Vertical and Horizontal Stretching and Refle ting Suppose c . 1. To obtain the
graph of y − cf sxd, stretch the graph of y − f sxd vertically by a factor of c y − s1ycdf sxd, shrink the graph of y − f sxd vertically by a factor of c y − f scxd, shrink the graph of y − f sxd horizontally by a factor of c y − f sxycd, stretch the graph of y − f sxd horizontally by a factor of c y − 2f sxd, reflect the graph of y − f sxd about the xaxis y − f s2xd, reflect the graph of y − f sxd about the yaxis
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38
CHAPTER 1 Functions and Models
Figure 3 illustrates these stretching transformations when applied to the cosine function with c − 2. For instance, in order to get the graph of y − 2 cos x we multiply the ycoordinate of each point on the graph of y − cos x by 2. This means that the graph of y − cos x gets stretched vertically by a factor of 2. y
y=2 cos x
y
2
y=cos x
2
1
1 y= 2
0
cos x
y=cos 1 x
y=cos 2x
2
1 x
1
0
x
y=cos x
FIGURE 3
EXAMPLE 1 Given the graph of y − sx , use transformations to graph y − sx 2 2, y − sx 2 2 , y − 2sx , y − 2sx , and y − s2x .
SOLUTION The graph of the square root function y − sx , obtained from Figure 1.2.13(a), is shown in Figure 4(a). In the other parts of the figure we sketch y − sx 2 2 by shifting 2 units downward, y − sx 2 2 by shifting 2 units to the right, y − 2sx by reflecting about the xaxis, y − 2sx by stretching vertically by a factor of 2, and y − s2x by reflecting about the yaxis. y
y
y
y
y
y
1 0
x
1
x
0
0
x
2
x
0
x
0
0
x
_2
(a) y=œ„x
(b) y=œ„2 x
(d) y=_ œ„x
(c) y=œ„„„„ x2
(f ) y=œ„„ _x
(e) y=2 œ„x
FIGURE 4
■
EXAMPLE 2 Sketch the graph of the function f sxd − x 2 1 6x 1 10. SOLUTION Completing the square, we write the equation of the graph as y − x 2 1 6x 1 10 − sx 1 3d2 1 1 This means we obtain the desired graph by starting with the parabola y − x 2 and shifting 3 units to the left and then 1 unit upward (see Figure 5). y
y
1
(_3, 1) 0
FIGURE 5
(a) y=≈
x
_3
_1
0
(b) y=(x+3)@+1
x
■
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39
SECTION 1.3 New Functions from Old Functions
EXAMPLE 3 Sketch the graph of each function. (a) y − sin 2x (b) y − 1 2 sin x SOLUTION (a) We obtain the graph of y − sin 2x from that of y − sin x by compressing horizontally by a factor of 2. (See Figures 6 and 7.) Because the period of y − sin x is 2, the period of y − sin 2x is 2y2 − . y
y
y=sin x
1 0
π 2
π
y=sin 2x
1 2π
x
0 π π 4
FIGURE 6
x
π
2
FIGURE 7
(b) To obtain the graph of y − 1 2 sin x, we again start with y − sin x. We reflect about the xaxis to get the graph of y − 2sin x and then we shift 1 unit upward to get y − 1 2 sin x. (See Figure 8.) y
y=1sin x
2 1 0
FIGURE 8
π 2
π
3π 2
x
2π
■
EXAMPLE 4 Figure 9 shows graphs of the number of hours of daylight as functions of the time of the year at several latitudes. Given that Philadelphia is located at approximately 408N latitude, find a function that models the length of daylight at Philadelphia. 20 18 16 14 12
20° N 30° N 40° N 50° N
Hours 10 8
FIGURE 9 Graph of the length of daylight from March 21 through December 21 at various latitudes Source: Adapted from L. Harrison, Daylight, Twilight, Darkness and Time (New York: Silver, Burdett, 1935), 40.
6
60° N
4 2 0
Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec.
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40
CHAPTER 1 Functions and Models
SOLUTION Notice that each curve resembles a shifted and stretched sine function. By looking at the blue curve we see that, at the latitude of Philadelphia, daylight lasts about 14.8 hours on June 21 and 9.2 hours on December 21, so the amplitude of the curve (the factor by which we have to stretch the sine curve vertically) is 1 2 s14.8 2 9.2d − 2.8. By what factor do we need to stretch the sine curve horizontally if we measure the time t in days? Because there are about 365 days in a year, the period of our model should be 365. But the period of y − sin t is 2, so the horizontal stretching factor is 2y365. We also notice that the curve begins its cycle on March 21, the 80th day of the year, so we have to shift the curve 80 units to the right. In addition, we shift it 12 units upward. Therefore we model the length of daylight in Philadelphia on the t th day of the year by the function 2 Lstd − 12 1 2.8 sin st 2 80d 365 ■
F
y
_1
0
1
x
(a) y=≈1
_1
Another transformation of some interest is taking the absolute value of a function. If y − f sxd , then according to the definition of absolute value, y − f sxd when f sxd > 0 and y − 2f sxd when f sxd , 0. This tells us how to get the graph of y − f sxd from the graph of y − f sxd: the part of the graph that lies above the xaxis remains the same, and the part that lies below the xaxis is reflected about the xaxis.




y
EXAMPLE 5 Sketch the graph of the function y −  x 2 2 1 .
0
SOLUTION We first graph the parabola y − x 2 2 1 in Figure 10(a) by shifting the parabola y − x 2 downward 1 unit. We see that the graph lies below the xaxis when 21 , x , 1, so we reflect that part of the graph about the xaxis to obtain the graph of y − x 2 2 1 in Figure 10(b). ■
1
(b) y= ≈1 
FIGURE 10
G
x


■ Combinations of Functions Two functions f and t can be combined to form new functions f 1 t, f 2 t, ft, and fyt in a manner similar to the way we add, subtract, multiply, and divide real numbers. Definitio Given two functions f and t, the sum, difference, product, and quotient functions are defined by s f 1 tdsxd − f sxd 1 tsxd s f 2 tdsxd − f sxd 2 tsxd s ftdsxd − f sxd tsxd
SD
f f sxd sxd − t tsxd
If the domain of f is A and the domain of t is B, then the domain of f 1 t (and the domain of f 2 t) is the intersection A > B because both f sxd and tsxd have to be defined. For example, the domain of f sxd − sx is A − f0, `d and the domain of tsxd − s2 2 x is B − s2`, 2g, so the domain of s f 1 tdsxd − sx 1 s2 2 x is A > B − f0, 2g. The domain of ft is also A > B. Because we can’t divide by 0, the domain of fyt is hx [ A > B tsxd ± 0j. For instance, if f sxd − x 2 and tsxd − x 2 1, then the domain of the rational function s fytdsxd − x 2ysx 2 1d is hx x ± 1j, or s2`, 1d ø s1, `d. There is another way of combining two functions to obtain a new function. For example, suppose that y − f sud − su and u − tsxd − x 2 1 1. Since y is a function


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SECTION 1.3 New Functions from Old Functions
41
of u and u is, in turn, a function of x, it follows that y is ultimately a function of x. We compute this by substitution: y − f sud − f stsxdd − f sx 2 1 1d − sx 2 1 1 x (input)
g
©
f•g
The procedure is called composition because the new function is composed of the two given functions f and t. In general, given any two functions f and t, we start with a number x in the domain of t and calculate tsxd. If this number tsxd is in the domain of f, then we can calculate the value of f stsxdd. Notice that the output of one function is used as the input to the next function. The result is a new function hsxd − f s tsxdd obtained by substituting t into f. It is called the composition (or composite) of f and t and is denoted by f 8 t (“ f circle t”). Definitio Given two functions f and t, the composite function f 8 t (also called the composition of f and t) is defined by
f
s f 8 tdsxd − f stsxdd
f { ©} (output)
FIGURE 11
The f 8 t machine is composed of the t machine (first) and then the f machine.
The domain of f 8 t is the set of all x in the domain of t such that tsxd is in the domain of f. In other words, s f 8 tdsxd is defined whenever both tsxd and f stsxdd are defined. Figure 11 shows how to picture f 8 t in terms of machines.
EXAMPLE 6 If f sxd − x 2 and tsxd − x 2 3, find the composite functions f 8 t and t 8 f. SOLUTION We have s f 8 tdsxd − f stsxdd − f sx 2 3d − sx 2 3d2
st 8 f dsxd − ts f sxdd − tsx 2 d − x 2 2 3
n
NOTE You can see from Example 6 that, in general, f 8 t ± t 8 f. Remember, the notation f 8 t means that the function t is applied first and then f is applied second. In Example 6, f 8 t is the function that first subtracts 3 and then squares; t 8 f is the function that first squares and then subtracts 3.
EXAMPLE 7 If f sxd − sx and tsxd − s2 2 x , find each function and its domain.
(a) f 8 t (b) t 8 f (c) f 8 f (d) t 8 t SOLUTION 4 (a) s f 8 tdsxd − f stsxdd − f (s2 2 x ) − ss2 2 x − s 22x


The domain of f 8 t is hx 2 2 x > 0j − hx x < 2j − s2`, 2g. (b) If 0 < a < b, then a 2 < b 2.
st 8 f dsxd − ts f sxdd − t (sx ) − s2 2 sx
For sx to be defined we must have x > 0. For s2 2 sx to be defined we must have 2 2 sx > 0, that is, sx < 2, or x < 4. Thus we have 0 < x < 4, so the domain of t 8 f is the closed interval f0, 4g. (c)
4 s f 8 f dsxd − f s f sxdd − f (sx ) − ssx − s x
The domain of f 8 f is f0, `d.
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42
CHAPTER 1 Functions and Models
st 8 tdsxd − tstsxdd − t (s2 2 x ) − s2 2 s2 2 x
(d)
This expression is defined when both 2 2 x > 0 and 2 2 s2 2 x > 0. The first inequality means x < 2, and the second is equivalent to s2 2 x < 2, or 2 2 x < 4, or x > 22. Thus 22 < x < 2, so the domain of t 8 t is the closed interval f22, 2g. ■ It is possible to take the composition of three or more functions. For instance, the composite function f 8 t 8 h is found by first applying h, then t, and then f as follows: s f 8 t 8 hdsxd − f stshsxddd
EXAMPLE 8 Find f 8 t 8 h if f sxd − xysx 1 1d, tsxd − x 10, and hsxd − x 1 3. SOLUTION
s f 8 t 8 hdsxd − f stshsxddd − f stsx 1 3dd sx 1 3d10 − f ssx 1 3d10 d − sx 1 3d10 1 1
■
So far we have used composition to build complicated functions from simpler ones. But in calculus it is often useful to be able to decompose a complicated function into simpler ones, as in the following example.
EXAMPLE 9 Given Fsxd − cos2sx 1 9d, find functions f , t, and h such that F − f 8 t 8 h. SOLUTION Since Fsxd − fcossx 1 9dg 2, the formula for F says: first add 9, then take the cosine of the result, and finally square. So we let hsxd − x 1 9 tsxd − cos x f sxd − x 2 Then
s f 8 t 8 hdsxd − f stshsxddd − f stsx 1 9dd − f scossx 1 9dd − fcossx 1 9dg 2 − Fsxd
■
1.3 Exercises 1. Suppose the graph of f is given. Write equations for the graphs that are obtained from the graph of f as follows. (a) Shift 3 units upward.
3. The graph of y − f sxd is given. Match each equation with its graph and give reasons for your choices. (a) y − f sx 2 4d (b) y − f sxd 1 3
(b) Shift 3 units downward.
(c) y − 13 f sxd (d) y − 2f sx 1 4d
(c) Shift 3 units to the right.
(e) y − 2 f sx 1 6d
(d) Shift 3 units to the left.
(e) Reflect about the xaxis.
(f ) Reflect about the yaxis.
(g) Stretch vertically by a factor of 3.
(h) Shrink vertically by a factor of 3.
2. Explain how each graph is obtained from the graph of y − f sxd. (a) y − f sxd 1 8 (b) y − f sx 1 8d (c) y − 8 f sxd (d) y − f s8xd (e) y − 2f sxd 2 1 (f) y − 8 f ( 18 x)
y
@
6
3
! f
#
$ _6
_3
%
0
3
6
x
_3
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SECTION 1.3 New Functions from Old Functions
4. The graph of f is given. Draw the graphs of the following functions. (a) y − f sxd 2 3 (b) y − f sx 1 1d 1 2
(c) y − f sxd (d) y − 2f sxd y
13. y −
1 12 x
14. y − 2sx 2 1
0
1
x
16. y − 1 1
17. y − 2 1 sx 1 1
18. y − 2sx 2 1d2 1 3
19. y − x 2 2 2x 1 5
20. y − sx 1 1d3 1 2
21. y − 2 2 x
22. y − 2 2 2 cos x
23. y − 3 sin 12 x 1 1
24. y −

26. y − sx 2 1
y 1 x
1
–7 The graph of y − s3x 2 x 2 is given. Use transformations 6 to create a function whose graph is as shown. y
y=œ„„„„„„ 3x≈
1.5 0
x
3
6. y 3
7.
y _4
0
5
2
_1 0
x _1 _2.5
x
8. (a) How is the graph of y − 1 1 sx related to the graph of y − sx ? Use your answer and Figure 4(a) to sketch the graph of y − 1 1 sx . (b) How is the graph of y − 5 sin x related to the graph of y − sin x ? Use your answer and Figure 6 to sketch the graph of y − 5 sin x . 9–26 Graph the function by hand, not by plotting points, but by starting with the graph of one of the standard functions given in Table 1.2.3, and then applying the appropriate transformations. 9. y − 1 1 x 2


11. y − x 1 2
10. y − sx 1 1d2

27. The city of New Orleans is located at latitude 30°N. Use Figure 9 to find a function that models the number of hours of daylight at New Orleans as a function of the time of year. To check the accuracy of your model, use the fact that on March 31 the sun rises at 5:51 am and sets at 6:18 pm in New Orleans.
(c) y − f s2xd (d) y − 2f s2xd
0
S D
1 tan x 2 4 4


25. y − cos x 5. The graph of f is given. Use it to graph the following functions. (a) y − f s2xd (b) y − f ( 12 x)
1 x2
15. y − sin 4x
 
2
43
28. A variable star is one whose brightness alternately increases and decreases. For the most visible variable star, Delta Cephei, the time between periods of maximum brightness is 5.4 days, the average brightness (or magnitude) of the star is 4.0, and its brightness varies by 60.35 magnitude. Find a function that models the brightness of Delta Cephei as a function of time. 29. Some of the highest tides in the world occur in the Bay of Fundy on the Atlantic Coast of Canada. At Hopewell Cape the water depth at low tide is about 2.0 m and at high tide it is about 12.0 m. The natural period of oscillation is about 12 hours and on a particular day, high tide occurred at 6:45 am. Find a function involving the cosine function that models the water depth Dstd (in meters) as a function of time t (in hours after midnight) on that day. 30. In a normal respiratory cycle the volume of air that moves into and out of the lungs is about 500 mL. The reserve and residue volumes of air that remain in the lungs occupy about 2000 mL and a single respiratory cycle for an average human takes about 4 seconds. Find a model for the total volume of air Vstd in the lungs as a function of time.
     
31. (a) How is the graph of y − f ( x ) related to the graph of f ? (b) Sketch the graph of y − sin x . (c) Sketch the graph of y − s x . 32. Use the given graph of f to sketch the graph of y − 1yf sxd. Which features of f are the most important in sketching y − 1yf sxd? Explain how they are used. y 1 0
1
x
12. y − 1 2 x 3
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44
CHAPTER 1 Functions and Models
33–34 Find (a) f 1 t, (b) f 2 t, (c) f t, and (d) fyt and state their domains. 33. f sxd − s25 2 x 2, tsxd − sx 1 1 1 1 , tsxd − 2 2 x21 x
34. f sxd −
35– 40 Find the functions (a) f 8 t, (b) t 8 f , (c) f 8 f , and (d) t 8 t and their domains.
56. (a) ts ts ts2ddd (b) s f + f + f ds1d s t + f + tds3d (c) s f + f + tds1d (d) 57. Use the given graphs of f and t to evaluate each expression, or explain why it is undefined. (a) f s ts2dd (b) ts f s0dd (c) s f 8 tds0d (d) s t 8 f ds6d (e) s t 8 tds22d (f) s f 8 f ds4d y
35. f sxd − x 1 5, tsxd − sx 3
3
g
1 , tsxd − 2x 1 1 x
36. f sxd −
1
37. f sxd −
sx
2
, tsxd − x 1 1
0
x 38. f sxd − , tsxd − 2x 2 1 x11 2 , tsxd − sin x x
39. f sxd −
y
41– 44 Find f 8 t 8 h.
g
41. f sxd − 3x 2 2, tsxd − sin x, hsxd − x 2
1

42. f sxd − x 2 4 , tsxd − 2 x, hsxd − sx
0
43. f sxd − sx 2 3 , tsxd − x 2, hsxd − x 3 1 2 44. f sxd − tan x, tsxd −
x 3 x , hsxd − s x21
45. Fsxd − s2 x 1 x 2 d 4 3 x s
1 1 sx 3
46. Fsxd − cos2 x
48. Gsxd −
49. v std − secst 2 d tanst 2 d
Î 3
x 11x
50. Hsxd − s1 1 sx
51–54 Express the function in the form f 8 t 8 h. 8 51. Rsxd − ssx 2 1 52. Hsxd − s 21 x
 
54. Hstd − cos (s tan t 1 1)
53. Sstd − sin2scos td
1
x
f
45–50 Express the function in the form f 8 t.
47. Fsxd −
x
2
58. Use the given graphs of f and t to estimate the value of f s tsxdd for x − 25, 24, 23, . . . , 5. Use these estimates to sketch a rough graph of f 8 t.
40. f sxd − s5 2 x , tsxd − sx 2 1

f
55–56 Use the table to evaluate each expression. x
1
2
3
4
5
6
f sxd
3
1
5
6
2
4
tsxd
5
3
4
1
3
2
ts f s2dd 55. (a) f s ts3dd (b) (c) s f 8 tds5d (d) s t 8 f ds5d
59. A stone is dropped into a lake, creating a circular ripple that travels outward at a speed of 60 cmys. (a) Express the radius r of this circle as a function of the time t (in seconds). (b) If A is the area of this circle as a function of the radius, find A 8 r and interpret it. 60. A spherical balloon is being inflated and the radius of the balloon is increasing at a rate of 2 cmys. (a) Express the radius r of the balloon as a function of the time t (in seconds). (b) If V is the volume of the balloon as a function of the radius, find V 8 r and interpret it. 61. A ship is moving at a speed of 30 kmyh parallel to a straight shoreline. The ship is 6 km from shore and it passes a lighthouse at noon. (a) Express the distance s between the lighthouse and the ship as a function of d, the distance the ship has traveled since noon; that is, find f so that s − f sd d. (b) Express d as a function of t, the time elapsed since noon; that is, find t so that d − tstd. (c) Find f 8 t. What does this function represent?
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SECTION 1.4 Exponential Functions
62. An airplane is flying at a speed of 560 kmyh at an altitude of two kilometers and passes directly over a radar station at time t − 0. (a) Express the horizontal distance d (in kilometers) that the plane has flown as a function of t. (b) Express the distance s between the plane and the radar station as a function of d. (c) Use composition to express s as a function of t. 63. The Heaviside Function The Heaviside function H is defined by
H
0 if t , 0 Hstd − 1 if t > 0
It is used in the study of electric circuits to represent the sudden surge of electric current, or voltage, when a switch is instantaneously turned on. (a) Sketch the graph of the Heaviside function. (b) Sketch the graph of the voltage Vstd in a circuit if the switch is turned on at time t − 0 and 120 volts are applied instantaneously to the circuit. Write a formula for Vstd in terms of Hstd. (c) Sketch the graph of the voltage Vstd in a circuit if the switch is turned on at time t − 5 seconds and 240 volts are applied instantaneously to the circuit. Write a formula for Vstd in terms of Hstd. (Note that starting at t − 5 corresponds to a translation.)
64. The Ramp Function The Heaviside function defined in Exercise 63 can also be used to define the ramp function y − ctHstd, which represents a gradual increase in voltage or current in a circuit. (a) Sketch the graph of the ramp function y − tHstd. (b) Sketch the graph of the voltage Vstd in a circuit if the switch is turned on at time t − 0 and the voltage is gradually increased to 120 volts over a 60second time interval. Write a formula for Vstd in terms of Hstd for t < 60.
45
(c) Sketch the graph of the voltage Vstd in a circuit if the switch is turned on at time t − 7 seconds and the voltage is gradually increased to 100 volts over a period of 25 seconds. Write a formula for Vstd in terms of Hstd for t < 32.
65. Let f and t be linear functions with equations f sxd − m1 x 1 b1 and tsxd − m 2 x 1 b 2. Is f 8 t also a linear function? If so, what is the slope of its graph? 66. I f you invest x dollars at 4% interest compounded annually, then the amount Asxd of the investment after one year is Asxd − 1.04x. Find A 8 A, A 8 A 8 A, and A 8 A 8 A 8 A. What do these compositions represent? Find a formula for the composition of n copies of A. 67. (a) If tsxd − 2x 1 1 and hsxd − 4x 2 1 4x 1 7, find a function f such that f 8 t − h. (Think about what operations you would have to perform on the formula for t to end up with the formula for h.) (b) If f sxd − 3x 1 5 and hsxd − 3x 2 1 3x 1 2, find a function t such that f 8 t − h. 68. If f sxd − x 1 4 and hsxd − 4x 2 1, find a function t such that t 8 f − h. 69. Suppose t is an even function and let h − f 8 t. Is h always an even function? 70. Suppose t is an odd function and let h − f 8 t. Is h always an odd function? What if f is odd? What if f is even? 71.
Let f sxd be a function with domain R . (a) Show that Esxd − f sxd 1 f s2xd is an even function. (b) Show that Osxd − f sxd 2 f s2xd is an odd function. (c) Prove that every function f sxd can be written as a sum of an even function and an odd function. (d) Express the function f sxd − 2 x 1 sx 2 3d2 as a sum of an even function and an odd function.
1.4 Exponential Functions The function f sxd − 2 x is called an exponential function because the variable, x, is the exponent. It should not be confused with the power function tsxd − x 2, in which the variable is the base.
■ Exponential Functions and Their Graphs In general, an exponential function is a function of the form f sxd − b x In Appendix G we present an alternative approach to the exponential and logarithmic functions using integral calculus.
where b is a positive constant. Let’s recall what this means. If x − n, a positive integer, then bn − b ? b ? ∙ ∙ ∙ ? b n factors
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46
CHAPTER 1 Functions and Models
If x − 0, then b 0 − 1, and if x − 2n, where n is a positive integer, then b 2n − y
1 bn
If x is a rational number, x − pyq, where p and q are integers and q . 0, then q p q b x − b pyq − s b − (s b)
1 0
1
x
FIGURE 1 Representation of y − 2 x, x rational
p
But what is the meaning of b x if x is an irrational number? For instance, what is meant by 2 s3 or 5 ? To help us answer this question we first look at the graph of the function y − 2 x, where x is rational. A representation of this graph is shown in Figure 1. We want to enlarge the domain of y − 2 x to include both rational and irrational numbers. There are holes in the graph in Figure 1 corresponding to irrational values of x. We want to fill in the holes by defining f sxd − 2 x, where x [ R, so that f is an increasing function. In particular, since the irrational number s3 satisfies 1.7 , s3 , 1.8 2 1.7 , 2 s3 , 2 1.8
we must have
and we know what 21.7 and 21.8 mean because 1.7 and 1.8 are rational numbers. Similarly, if we use better approximations for s3 , we obtain better approximations for 2 s3:
A proof of this fact is given in J. Marsden and A. Weinstein, Calculus Unlimited (Menlo Park, CA: Benjamin/ Cummings, 1981).
1.73 , s3 , 1.74
?
2 1.73 , 2 s3 , 2 1.74
1.732 , s3 , 1.733
?
2 1.732 , 2 s3 , 2 1.733
1.7320 , s3 , 1.7321
?
2 1.7320 , 2 s3 , 2 1.7321
1.73205 , s3 , 1.73206 ? 2 1.73205 , 2 s3 , 2 1.73206 . . . . . . . . . . . .
It can be shown that there is exactly one number that is greater than all of the numbers 2 1.7, 2 1.73, 2 1.732, 2 1.7320, 2 1.73205, . . . and less than all of the numbers 2 1.8, 2 1.74, 2 1.733, 2 1.7321, 2 1.73206, . . . We define 2 s3 to be this number. Using the preceding approximation process we can compute it correct to six decimal places: 2 s3 < 3.321997 Similarly, we can define 2 x (or b x, if b . 0) where x is any irrational number. Figure 2 shows how all the holes in Figure 1 have been filled to complete the graph of the function f sxd − 2 x, x [ R. y
1
FIGURE 2 y − 2 x, x real
0
1
x
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SECTION 1.4 Exponential Functions
47
The graphs of members of the family of functions y − b x are shown in Figure 3 for various values of the base b. Notice that all of these graphs pass through the same point s0, 1d because b 0 − 1 for b ± 0. Notice also that as the base b gets larger, the exponential function grows more rapidly (for x . 0). ” 4 ’®
” 2 ’®
1
1
y
10®
4®
2®
If 0 , b , 1, then b x approaches 0 as x becomes large. If b . 1, then b x approaches 0 as x decreases through negative values. In both cases the xaxis is a horizontal asymptote. These matters are discussed in Section 2.6.
1.5®
1®
0
FIGURE 3
1
x
You can see from Figure 3 that there are basically three kinds of exponential functions y − b x. If 0 , b , 1, the exponential function decreases; if b − 1, it is a constant; and if b . 1, it increases. These three cases are illustrated in Figure 4. Observe that if b ± 1, then the exponential function y − b x has domain R and range s0, `d. Notice also that, since s1ybd x − 1yb x − b 2x, the graph of y − s1ybd x is just the reflection of the graph of y − b x about the yaxis. y
1
(0, 1) 0
FIGURE 4
y
y
(a) y=b ®, 0 0. So the graph of f 21 is the right half of the parabola y − 2x 2 2 1 and this seems reasonable from Figure 10. ■
■ Logarithmic Functions If b . 0 and b ± 1, the exponential function f sxd − b x is either increasing or decreasing and so it is onetoone by the Horizontal Line Test. It therefore has an inverse function f 21, which is called the logarithmic function with base b and is denoted by log b. If we use the formulation of an inverse function given by (3), f 21sxd − y &? f syd − x
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58
CHAPTER 1 Functions and Models
then we have log b x − y &? b y − x
6
Thus, if x . 0, then log b x is the exponent to which the base b must be raised to give x. For example, log10 0.001 − 23 because 1023 − 0.001. The cancellation equations (4), when applied to the functions f sxd − b x and 21 f sxd − log b x, become log b sb x d − x for every x [ R
7
y
y=x
y=b®, b>1 0
x
b log x − x for every x . 0 b
The logarithmic function log b has domain s0, `d and range R. Its graph is the reflection of the graph of y − b x about the line y − x. Figure 11 shows the case where b . 1. (The most important logarithmic functions have base b . 1.) The fact that y − b x is a very rapidly increasing function for x . 0 is reflected in the fact that y − log b x is a very slowly increasing function for x . 1. Figure 12 shows the graphs of y − log b x with various values of the base b . 1. Because log b 1 − 0, the graphs of all logarithmic functions pass through the point s1, 0d. y
y=log b x, b>1
y=log™ x y=log£ x
1
FIGURE 11
0
x
1
y=log¡¸ x
y=log∞ x
FIGURE 12
The following properties of logarithmic functions follow from the corresponding properties of exponential functions given in Section 1.4. Laws of Logarithms If x and y are positive numbers, then 1. log b sxyd − log b x 1 log b y 2. log b
SD x y
− log b x 2 log b y
3. log b sx r d − r log b x (where r is any real number)
EXAMPLE 6 Use the laws of logarithms to evaluate log 2 80 2 log 2 5. SOLUTION Using Law 2, we have log 2 80 2 log 2 5 − log 2 because 2 4 − 16.
S D 80 5
− log 2 16 − 4 ■
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SECTION 1.5 Inverse Functions and Logarithms
59
■ Natural Logarithms Notation for Logarithms Most textbooks in calculus and the sciences, as well as calculators, use the notation ln x for the natural logarithm and log x for the “common logarithm,” log10 x. In the more advanced mathematical and scientific literature and in computer languages, however, the notation log x usually denotes the natural logarithm.
Of all possible bases b for logarithms, we will see in Chapter 3 that the most convenient choice of a base is the number e, which was defined in Section 1.4. The logarithm with base e is called the natural logarithm and has a special notation: log e x − ln x
If we set b − e and replace log e with “ln” in (6) and (7), then the defining properties of the natural logarithm function become 8
ln x − y &? e y − x
lnse x d − x
9
e
ln x
−x
x[R x.0
In particular, if we set x − 1, we get ln e − 1
Combining Property 9 with Law 3 allows us to write r
x r − e ln sx d − e r ln x
x.0
Thus a power of x can be expressed in an equivalent exponential form; we will find this useful in the chapters to come. 10
x r − e r ln x
EXAMPLE 7 Find x if ln x − 5. SOLUTION 1 From (8) we see that ln x − 5 means e 5 − x Therefore x − e 5. (If you have trouble working with the “ln” notation, just replace it by log e . Then the equation becomes log e x − 5; so, by the definition of logarithm, e 5 − x.) SOLUTION 2 Start with the equation ln x − 5 and apply the exponential function to both sides of the equation: e ln x − e 5 But the second cancellation equation in (9) says that e ln x − x. Therefore x − e 5. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
■
60
CHAPTER 1 Functions and Models
EXAMPLE 8 Solve the equation e 523x − 10. SOLUTION We take natural logarithms of both sides of the equation and use (9): lnse 523x d − ln 10 5 2 3x − ln 10 3x − 5 2 ln 10 x − 13 s5 2 ln 10d Using a calculator, we can approximate the solution: to four decimal places, x < 0.8991.
■
The laws of logarithms allow us to expand logarithms of products and quotients as sums and differences of logarithms. These same laws also allow us to combine sums and differences of logarithms into a single logarithmic expression. These processes are illustrated in Examples 9 and 10.
EXAMPLE 9 Use the laws of logarithms to expand ln
x 2sx 2 1 2 . 3x 1 1
SOLUTION Using Laws 1, 2, and 3 of logarithms, we have ln
x 2sx 2 1 2 − ln x 2 1 ln sx 2 1 2 2 lns3x 1 1d 3x 1 1 − 2 ln x 1 12 lnsx 2 1 2d 2 lns3x 1 1d
■
EXAMPLE 10 Express ln a 1 12 ln b as a single logarithm. SOLUTION Using Laws 3 and 1 of logarithms, we have ln a 1 12 ln b − ln a 1 ln b 1y2 − ln a 1 lnsb
− ln ( asb
)
■
The following formula shows that logarithms with any base can be expressed in terms of the natural logarithm. 11 Change of Base Formula For any positive number b sb ± 1d, we have log b x −
ln x ln b
PROOF Let y − log b x. Then, from (6), we have b y − x. Taking natural logarithms of both sides of this equation, we get y ln b − ln x. Therefore
y−
ln x ln b
■
Formula 11 enables us to use a calculator to compute a logarithm with any base (as shown in the following example). Similarly, Formula 11 allows us to graph any logarithmic function on a graphing calculator or computer (see Exercises 49 and 50). Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
61
SECTION 1.5 Inverse Functions and Logarithms y
y=´
EXAMPLE 11 Evaluate log 8 5 correct to six decimal places. SOLUTION Formula 11 gives
y=x
1
y=ln x
0
x
1
FIGURE 13 The graph of y − ln x is the reflection of the graph of y − e x about the line y − x.
log 8 5 −
The graphs of the exponential function y − e x and its inverse function, the natural logarithm function, are shown in Figure 13. In common with all other logarithmic functions with base greater than 1, the natural logarithm is an increasing function defined on s0, `d and the yaxis is a vertical asymptote. (This means that the values of ln x become very large negative as x approaches 0.)
EXAMPLE 12 Sketch the graph of the function y − lnsx 2 2d 2 1. SOLUTION We start with the graph of y − ln x as given in Figure 13. Using the transformations of Section 1.3, we shift it 2 units to the right to get the graph of y − lnsx 2 2d and then we shift it 1 unit downward to get the graph of y − lnsx 2 2d 2 1. (See Figure 14.) y
y
x=2
y=ln x (1, 0)
■
■ Graph and Growth of the Natural Logarithm
y
0
ln 5 < 0.773976 ln 8
x=2 y=ln(x2)1
y=ln(x2) 0
x
2
x
(3, 0)
0
2
x (3, _1)
FIGURE 14
■
Although ln x is an increasing function, it grows very slowly when x . 1. In fact, ln x grows more slowly than any positive power of x. To illustrate this fact, we graph y − ln x and y − x 1y2 − sx in Figures 15 and 16. You can see that the graphs initially grow at comparable rates, but eventually the root function far surpasses the logarithm. y
y 20
x y=œ„ 1 0
y=ln x
y=ln x 1
x y=œ„
x
FIGURE 15
0
1000 x
FIGURE 16
■ Inverse Trigonometric Functions When we try to find the inverse trigonometric functions, we have a slight difficulty: because the trigonometric functions are not onetoone, they don’t have inverse functions. The difficulty is overcome by restricting the domains of these functions so that they become onetoone. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
62
CHAPTER 1 Functions and Models
You can see from Figure 17 that the sine function y − sin x is not onetoone (use the Horizontal Line Test). However, if we restrict the domain to the interval f2y2, y2, then the function is onetoone and all values in the range of y − sin x are attained (see Figure 18). The inverse function of this restricted sine function f exists and is denoted by sin 21 or arcsin. It is called the inverse sine function or the arcsine function. y
0
_π
FIGURE 17
y
y=sin x π 2
_ π2 0
x
π
π 2
x
FIGURE 18
y − sin x, 22 < x < 2
Since the definition of an inverse function says that f 21sxd − y &? f syd − x we have
sin21x ±
1 sin x
sin21x − y &? sin y − x and 2
1) &? sec y − x
12 y − csc21x
and y [ s0, y2g ø s, 3y2g
y − sec
and y [ f0, y2d ø f, 3y2d
y − cot21x sx [ Rd &? cot y − x and y [ s0, d
21
The choice of intervals for y in the definitions of csc21 and sec21 is not universally agreed upon. For instance, some authors use y [ f0, y2d ø sy2, g in the definition of sec21. [You can see from the graph of the secant function in Figure 26 that both this choice and the one in (12) will work.]
FIGURE 26 y − sec x
1.5 E xercises 1. (a) What is a onetoone function? (b) How can you tell from the graph of a function whether it is onetoone? 2. (a) Suppose f is a onetoone function with domain A and range B. How is the inverse function f 21 defined? What is the domain of f 21 ? What is the range of f 21 ? (b) If you are given a formula for f, how do you find a formula for f 21 ? (c) If you are given the graph of f, how do you find the graph of f 21 ? 3–16 A function is given by a table of values, a graph, a formula, or a verbal description. Determine whether it is onetoone. 3.
4.
x
1
2
3
4
5
6
f sxd
1.5
2.0
3.6
5.3
2.8
2.0
x
1
2
3
4
5
6
1.0
1.9
2.8
3.5
f sxd
y y
5.
6.
3.1 y y
x
y y
x
11. r std − t 3 1 4
3 12. tsxd − s x
13. tsxd − 1 2 sin x
14. f sxd − x 4 2 1, 0 ⩽ x ⩽ 10
15. f std is the height of a football t seconds after kickoff. 16. f std is your height at age t. 17. A ssume that f is a onetoone function. (a) If f s6d − 17, what is f 21s17d? (b) If f 21s3d − 2, what is f s2d? 18. If f sxd − x 5 1 x 3 1 x, find f 21s3d and f s f 21s2dd. 20.
2.9
The graph of f is given. (a) Why is f onetoone? (b) What are the domain and range of f 21 ? (c) What is the value of f 21s2d? (d) Estimate the value of f 21s0d. y
x x
1 0
8.
x
10. f sxd − x 4 2 16
19. If tsxd − 3 1 x 1 e x, find t21s4d.
x
7.
9. f sxd − 2x 2 3
1
x
y y
x x
21. T he formula C − 59 sF 2 32d, where F > 2459.67, expresses the Celsius temperature C as a function of the Fahrenheit temperature F. Find a formula for the inverse function and interpret it. What is the domain of the inverse function?
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65
SECTION 1.5 Inverse Functions and Logarithms
22. In the theory of relativity, the mass of a particle with speed v is m0 m − f sv d − 2 s1 v 2yc 2 where m 0 is the rest mass of the particle and c is the speed of light in a vacuum. Find the inverse function of f and explain its meaning. 23–30 Find a formula for the inverse of the function. 23. f sxd − 1 2 x 2, x > 0
24. tsxd − x 2 2 2 x, x > 1
25. tsxd − 2 1 sx 1 1
26. hsxd −
27. y − e 12x
28. y − 3 lnsx 2 2d
6 2 3x 5x 1 7
5
30. y −
y
34. y
1 1 0
1 0 1
0 1
x
x
y 1 0
2
2
(c) log 9 3
(b) ln se (c) ln(ln e e ) 50
41. (a) log 2 30 2 log 2 15 (b) log 3 10 2 log 3 5 2 log 3 18 (c) 2 log 5 100 2 4 log 5 50 42. (a) e 3 ln 2
44. (a) ln
32. f sxd − 1 1 e2x
y
1 e2
Î
12e 1 1 e2x
33–34 Use the given graph of f to sketch the graph of f 21. 33.
40. (a) ln
1 ) (b) log3 ( 81
(c) e ln sln e
(b) e22 ln 5
x
S
x4 43. (a) log10 sx 2 y 3zd (b) ln sx 2 2 4
21 ; 31–32 Find an explicit formula for f and use it to graph 21 f , f, and the line y − x on the same screen. To check your work, see whether the graphs of f and f 21 are reflections about the line.
31. f sxd − s4 x 1 3
39. (a) log3 81
3d
43–44 Use the laws of logarithms to expand each expression.
2x
3 29. y − (2 1 s x)
39–42 Find the exact value of each expression.
x
D
3x 3 (b) log 2 fsx 3 1 1d ssx 2 3d2 g x23
45–46 Express as a single logarithm. 45. (a) log 10 20 2 13 log 10 1000
(b) ln a 2 2 ln b 1 3 ln c
2
46. (a) 3 lnsx 2 2d 2 lnsx 2 5x 1 6d 1 2 lnsx 2 3d (b) c log a x 2 d log a y 1 log a z 47–48 Use Formula 11 to evaluate each logarithm correct to six decimal places. 47. (a) log 5 10
(b) log15 12
48. (a) log3 12
(b) log12 6
; 49–50 Use Formula 11 to graph the given functions on a common screen. How are these graphs related? 49. y − log 1.5 x, y − ln x, y − log 10 x, y − log 50 x
35. L et f sxd − s1 2 x 2 , 0 < x < 1. (a) Find f 21. How is it related to f ? (b) Identify the graph of f and explain your answer to part (a). 3 36. L et tsxd − s 1 2 x3 . 21 (a) Find t . How is it related to t ? (b) Graph t. How do you explain your answer to part (a)? ;
37.
( a) How is the logarithmic function y − log b x defined? (b) What is the domain of this function? (c) What is the range of this function? (d) Sketch the general shape of the graph of the function y − log b x if b . 1.
38. (a) What is the natural logarithm? (b) What is the common logarithm? (c) Sketch the graphs of the natural logarithm function and the natural exponential function with a common set of axes.
50. y − ln x, y − log 8 x, y − e x, y − 8 x 51. Suppose that the graph of y − log 2 x is drawn on a coordinate grid where the unit of measurement is a centimeter. How many kilometers to the right of the origin do we have to move before the height of the curve reaches 25 cm? 0.1 ; 52. Compare the functions f sxd − x and tsxd − ln x by graphing both functions in several viewing rectangles. When does the graph of f finally surpass the graph of t ?
53–54 Make a rough sketch by hand of the graph of each function. Use the graphs given in Figures 12 and 13 and, if necessary, the transformations of Section 1.3. 53. (a) y − log 10sx 1 5d (b) y − 2ln x
 
54. (a) y − lns2xd (b) y − ln x
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66
CHAPTER 1 Functions and Models
fired the capacitors discharge completely and then immediately begin recharging. The charge Q of the capacitors t seconds after the discharge is given by
55–56 (a) What are the domain and range of f ? (b) What is the xintercept of the graph of f ? (c) Sketch the graph of f. 55. f sxd − ln x 1 2
Qstd − Q 0 s1 2 e2tya d
56. f sxd − lnsx 2 1d 2 1
57–60 Solve each equation for x. Give both an exact value and a decimal approximation, correct to three decimal places. 57. (a) lns4x 1 2d − 3
(b) e 2x23 − 12
58. (a) log 2sx 2 2 x 2 1d − 2
(b) 1 1 e 4x11 − 20
59. (a) ln x 1 lnsx 2 1d − 0
(b) 5 122x − 9
60. (a) lnsln xd − 0
60 (b) −4 1 1 e2x
(The maximum charge capacity is Q 0 and t is measured in seconds.) (a) Find a formula for the inverse of this function and explain its meaning. (b) How long does it take to recharge the capacitors to 90% of capacity if a − 50 ?
69–74 Find the exact value of each expression. 69. (a) cos21 s21d (b) sin21s0.5d 70. (a) tan21 s3 (b) arctans21d 71. (a) csc21 s2 (b) arcsin 1 72. (a) sin21 (21ys2 ) (b) cos21 (s3 y2 )
61–62 Solve each inequality for x. 61. (a) ln x , 0
(b) e x . 5
73. (a) cot21(2s3 ) (b) sec21 2
62. (a) 1 , e 3x21 , 2
(b) 1 2 2 ln x , 3
5 74. (a) arcsinssins5y4dd (b) cos (2 sin21 (13 ))
63. ( a) Find the domain of f sxd − lnse x 2 3d. (b) Find f 21 and its domain. 64. (a) What are the values of e ln 300 and lnse 300 d? (b) Use your calculator to evaluate e ln 300 and lnse 300 d. What do you notice? Can you explain why the calculator has trouble? 65. Graph the function f sxd − sx 3 1 x 2 1 x 1 1 and explain why it is onetoone. Then use a computer algebra system to find an explicit expression for f 21sxd. (Your CAS will produce three possible expressions. Explain why two of them are irrelevant in this context.) 66. (a) If tsxd − x 6 1 x 4, x > 0, use a computer algebra sys tem to find an expression for t 21sxd. (b) Use the expression in part (a) to graph y − tsxd, y − x, and y − t 21sxd on the same screen. 67. If a bacteria population starts with 100 bacteria and doubles every three hours, then the number of bacteria after t hours is n − f std − 100 ∙ 2 ty3. (a) Find the inverse of this function and explain its meaning. (b) When will the population reach 50,000 ? 68. The National Ignition Facility at the Lawrence Livermore National Laboratory maintains the world’s largest laser facility. The lasers, which are used to start a nuclear fusion reaction, are powered by a capacitor bank that stores a total of about 400 megajoules of energy. When the lasers are
75. Prove that cosssin21 xd − s1 2 x 2 . 76–78 Simplify the expression. 76. tanssin21 xd
77. sinstan21 xd
78. sins2 arccos xd
; 7980 Graph the given functions on the same screen. How are these graphs related? 79. y − sin x, 2y2 < x < y2; y − sin21x; y − x 80. y − tan x, 2y2 , x , y2; y − tan21x; y − x 81. Find the domain and range of the function tsxd − sin21s3x 1 1d 21 ; 82. (a) Graph the function f sxd − sinssin xd and explain the appearance of the graph. (b) Graph the function tsxd − sin21ssin xd. How do you explain the appearance of this graph?
83. (a) If we shift a curve to the left, what happens to its reflection about the line y − x? In view of this geometric principle, find an expression for the inverse of tsxd − f sx 1 cd, where f is a onetoone function. (b) Find an expression for the inverse of hsxd − f scxd, where c ± 0.
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CHAPTER 1 Review
1
67
REVIEW
CONCEPT CHECK
Answers to the Concept Check are available at StewartCalculus.com.
1. (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How can you tell whether a given curve is the graph of a function?
9. Suppose that f has domain A and t has domain B. (a) What is the domain of f 1 t ? (b) What is the domain of f t ? (c) What is the domain of fyt ?
2. Discuss four ways of representing a function. Illustrate your discussion with examples.
10. How is the composite function f 8 t defined? What is its domain?
3. (a) What is an even function? How can you tell if a function is even by looking at its graph? Give three examples of an even function. (b) What is an odd function? How can you tell if a function is odd by looking at its graph? Give three examples of an odd function.
11. Suppose the graph of f is given. Write an equation for each of the graphs that are obtained from the graph of f as follows. (a) Shift 2 units upward. (b) Shift 2 units downward. (c) Shift 2 units to the right. (d) Shift 2 units to the left. (e) Reflect about the xaxis. (f ) Reflect about the yaxis. (g) Stretch vertically by a factor of 2. (h) Shrink vertically by a factor of 2. ( i ) Stretch horizontally by a factor of 2. ( j ) Shrink horizontally by a factor of 2.
4. What is an increasing function? 5. What is a mathematical model? 6. Give an example of each type of function. (a) Linear function (b) Power function (c) Exponential function (d) Quadratic function (e) Polynomial of degree 5 (f ) Rational function 7. Sketch by hand, on the same axes, the graphs of the following functions. (a) f sxd − x (b) tsxd − x 2 3 (c) hsxd − x (d) jsxd − x 4 8. Draw, by hand, a rough sketch of the graph of each function. (a) y − sin x (b) y − tan x (c) y − ex (d) y − ln x (e) y − 1yx (f ) y − x (g) y − sx (h) y − tan21 x
 
12. (a) What is a onetoone function? How can you tell if a function is onetoone by looking at its graph? (b) If f is a onetoone function, how is its inverse function f 21 defined? How do you obtain the graph of f 21 from the graph of f ? 13. (a) How is the inverse sine function f sxd − sin21 x defined? What are its domain and range? (b) How is the inverse cosine function f sxd − cos21 x defined? What are its domain and range? (c) How is the inverse tangent function f sxd − tan21 x defined? What are its domain and range?
TRUEFALSE QUIZ Determine whether the statement is true or false. If it is true, explain why. If it is false, explain why or give an example that disproves the statement.
9. If 0 , a , b, then ln a , ln b.
1. If f is a function, then f ss 1 td − f ssd 1 f std.
10. If x . 0, then sln xd6 − 6 ln x.
8. You can always divide by e x.
2. If f ssd − f std, then s − t. 3. If f is a function, then f s3xd − 3 f sxd.
11. If x . 0 and a . 1, then
4. If the function f has an inverse and f s2d − 3, then f 21s3d − 2.
12. tan21s21d − 3y4
5. A vertical line intersects the graph of a function at most once. 6. If f and t are functions, then f 8 t − t 8 f. 7. If f is onetoone, then f 21sxd −
1 . f sxd
13. tan21x −
ln x x − ln . ln a a
sin21x cos21x
14. If x is any real number, then sx 2 − x.
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68
CHAPTER 1 Functions and Models
EXERCISES 1. Let f be the function whose graph is given.
10. T he graph of f is given. Draw the graphs of the following functions. (a) y − f sx 2 8d (b) y − 2f sxd (c) y − 2 2 f sxd (d) y − 12 f sxd 2 1 21 (e) y − f sxd (f ) y − f 21sx 1 3d
y
f 1
y
x
1
1
(a) Estimate the value of f s2d. (b) Estimate the values of x such that f sxd − 3. (c) State the domain of f. (d) State the range of f. (e) On what interval is f increasing? (f ) Is f onetoone? Explain. (g) Is f even, odd, or neither even nor odd? Explain.
2. The graph of t is given. y
g
1 0 1
x
(a) State the value of ts2d. (b) Why is t onetoone? (c) Estimate the value of t21s2d. (d) Estimate the domain of t21. (e) Sketch the graph of t21.
3. If f sxd − x 2 2 2x 1 3, evaluate the difference quotient f sa 1 hd 2 f sad h 4. Sketch a rough graph of the yield of a crop as a function of the amount of fertilizer used. 5–8 Find the domain and range of the function. Write your answer in interval notation. 5. f sxd − 2ys3x 2 1d
6. tsxd − s16 2 x 4
7. hsxd − lnsx 1 6d
8. Fstd − 3 1 cos 2t
9. Suppose that the graph of f is given. Describe how the graphs of the following functions can be obtained from the graph of f. (a) y − f sxd 1 5 (b) y − f sx 1 5d (c) y − 1 1 2 f sxd (d) y − f sx 2 2d 2 2 (e) y − 2f sxd (f ) y − f 21sxd
0
1
x
11–18 Use transformations to sketch the graph of the function. 11. f sxd − x 3 1 2
12. f sxd − sx 2 3d2
13. y − sx 1 2
14. y − lnsx 1 5d
15. tsxd − 1 1 cos 2x
16. hsxd − 2e x 1 2
17. ssxd − 1 1 0.5 x
18. f sxd − b
2x ex 2 1
if x , 0 if x > 0
19. Determine whether f is even, odd, or neither even nor odd. (a) f sxd − 2x 5 2 3x 2 1 2 (b) f sxd − x 3 2 x 7 2 (c) f sxd − e2x (d) f sxd − 1 1 sin x (e) f sxd − 1 2 cos 2x (f ) f sxd − sx 1 1d2 20. Find an expression for the function whose graph consists of the line segment from the point s22, 2d to the point s21, 0d together with the top half of the circle with center the origin and radius 1. 21. I f f sxd − ln x and tsxd − x 2 2 9, find the functions (a) f 8 t, (b) t 8 f , (c) f 8 f , (d) t 8 t, and their domains. 22. Express the function Fsxd − 1ysx 1 sx as a composition of three functions. 23. Life expectancy has improved dramatically in recent decades. The table gives the life expectancy at birth (in years) of males born in the United States. Use a scatter plot to choose an appropriate type of model. Use your model to predict the life span of a male born in the year 2030. Birth year Life expectancy 1900 1910 1920 1930 1940 1950
48.3 51.1 55.2 57.4 62.5 65.6
Birth year Life expectancy 1960 1970 1980 1990 2000 2010
66.6 67.1 70.0 71.8 73.0 76.2
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 1 Review
24. A smallappliance manufacturer finds that it costs $9000 to produce 1000 toaster ovens a week and $12,000 to produce 1500 toaster ovens a week. (a) Express the cost as a function of the number of toaster ovens produced, assuming that it is linear. Then sketch the graph. (b) What is the slope of the graph and what does it represent? (c) What is the yintercept of the graph and what does it represent? 25. If f sxd − 2x 1 4 , find f x
s6d.
21
26. Find the inverse function of f sxd −
2x 1 3 . 1 2 5x
27. Use the laws of logarithms to expand each expression.
Î
x2 1 1 (a) ln x sx 1 1 (b) log 2 x21
31–36 Solve the equation for x. Give both an exact value and a decimal approximation, correct to three decimal places. 31. e 2x − 3 x
33. e e − 10 35. tan21s3x 2d −
30. (a) ln
(b) log 6 4 1 log 6 54
(c) tan(arcsin
1 (b) sinstan21 1d (c) 1023 log 4 e3
4
36. ln x 2 1 − lns5 1 xd 2 4
Pstd −
29–30 Find the exact value of each expression.
34. cos21 x − 2
37. The viral load for an HIV patient is 52.0 RNA copiesymL before treatment begins. Eight days later the viral load is half of the initial amount. (a) Find the viral load after 24 days. (b) Find the viral load Vstd that remains after t days. (c) Find a formula for the inverse of the function V and explain its meaning. (d) After how many days will the viral load be reduced to 2.0 RNA copiesymL?
(b) lnsx 2 3d 1 lnsx 1 3d 2 2 lnsx 2 2 9d
29. (a) e
32. ln x 2 − 5
38. The population of a certain species in a limited environment with initial population 100 and carrying capacity 1000 is
28. Express as a single logarithm. 1 2 (a) 2 ln x 2 2 lnsx 1 1d
2 ln 5
69
4 5
)
;
100,000 100 1 900e2t
where t is measured in years. (a) Graph this function and estimate how long it takes for the population to reach 900. (b) Find the inverse of this function and explain its meaning. (c) Use the inverse function to find the time required for the population to reach 900. Compare with the result of part (a).
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Principles of Problem Solving There are no hard and fast rules that will ensure success in solving problems. However, it is possible to outline some general steps in the problemsolving process and to give some principles that may be useful in the solution of certain problems. These steps and principles are just common sense made explicit. They have been adapted from George Polya’s book How To Solve It. 1 UNDERSTAND THE PROBLEM
The first step is to read the problem and make sure that you understand it clearly. Ask yourself the following questions: What is the unknown? What are the given quantities? What are the given conditions? For many problems it is useful to draw a diagram and identify the given and required quantities on the diagram. Usually it is necessary to introduce suitable notation In choosing symbols for the unknown quantities we often use letters such as a, b, c, m, n, x, and y, but in some cases it helps to use initials as suggestive symbols; for instance, V for volume or t for time.
2 THINK OF A PLAN
Find a connection between the given information and the unknown that will enable you to calculate the unknown. It often helps to ask yourself explicitly: “How can I relate the given to the unknown?” If you don’t see a connection immediately, the following ideas may be helpful in devising a plan. Try to Recognize Something Familiar Relate the given situation to previous knowledge. Look at the unknown and try to recall a more familiar problem that has a similar unknown. Try to Recognize Patterns Some problems are solved by recognizing that some kind of pattern is occurring. The pattern could be geometric, or numerical, or algebraic. If you can see regularity or repetition in a problem, you might be able to guess what the continuing pattern is and then prove it. Use Analogy Try to think of an analogous problem — that is, a similar problem, a related problem — but one that is easier than the original problem. If you can solve the similar, simpler problem, then it might give you the clues you need to solve the original, more difficult problem. For instance, if a problem involves very large numbers, you could first try a similar problem with smaller numbers. Or if the problem involves threedimensional geometry, you could look for a similar problem in twodimensional geometry. Or if the problem you start with is a general one, you could first try a special case. Introduce Something Extra It may sometimes be necessary to introduce something new — an auxiliary aid — to help make the connection between the given and the unknown. For instance, in a problem where a diagram is useful the auxiliary aid could be a new line drawn in a diagram. In a more algebraic problem it could be a new unknown that is related to the original unknown. Take Cases We may sometimes have to split a problem into several cases and give a different argument for each of the cases. For instance, we often have to use this strategy in dealing with absolute value.
70 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Work Backward Sometimes it is useful to imagine that your problem is solved and then to work backward, step by step, until you arrive at the given data. At this point you may be able to reverse your steps and thereby construct a solution to the original problem. This procedure is commonly used in solving equations. For instance, in solving the equation 3x 2 5 − 7, we suppose that x is a number that satisfies 3x 2 5 − 7 and work backward. We add 5 to each side of the equation and then divide each side by 3 to get x − 4. Since each of these steps can be reversed, we have solved the problem. Establish Subgoals In a complex problem it is often useful to set subgoals (in which the desired situation is only partially fulfilled). If we can first reach these subgoals, then we may be able to build on them to reach our final goal. Indirect Reasoning Sometimes it is appropriate to attack a problem indirectly. In using proof by contradiction to prove that P implies Q, we assume that P is true and Q is false and try to see why this can’t happen. Somehow we have to use this information and arrive at a contradiction to what we absolutely know is true. Mathematical Induction In proving statements that involve a positive integer n, it is frequently helpful to use the following principle.
Principle of Mathematical Induction Let Sn be a statement about the positive integer n. Suppose that 1. S1 is true.
2. Sk11 is true whenever Sk is true. Then Sn is true for all positive integers n. This is reasonable because, since S1 is true, it follows from condition 2 swith k − 1d that S2 is true. Then, using condition 2 with k − 2, we see that S3 is true. Again using condition 2, this time with k − 3, we have that S4 is true. This procedure can be followed indefinitely. 3 CARRY OUT THE PLAN
In Step 2 a plan was devised. In carrying out that plan we have to check each stage of the plan and write the details that prove that each stage is correct.
4 LOOK BACK
Having completed our solution, it is wise to look back over it, partly to see if we have made errors in the solution and partly to see if we can think of an easier way to solve the problem. Another reason for looking back is that it will familiarize us with the method of solution and this may be useful for solving a future problem. Descartes said, “Every problem that I solved became a rule which served afterwards to solve other problems.” These principles of problem solving are illustrated in the following examples. Before you look at the solutions, try to solve these problems yourself, referring to these prin ciples of problem solving if you get stuck. You may find it useful to refer to this section from time to time as you solve the exercises in the remaining chapters of this book.
EXAMPLE 1 Express the hypotenuse h of a right triangle with area 25 m2 as a function of its perimeter P. PS Understand the problem.
SOLUTION Let’s first sort out the information by identifying the unknown quantity and the data: Unknown: hypotenuse h Given quantities: perimeter P, area 25 m 2 71
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
PS Draw a diagram.
It helps to draw a diagram and we do so in Figure 1. h
FIGURE 1 PS Connect the given with the unknown. PS Introduce something extra.
b
a
In order to connect the given quantities to the unknown, we introduce two extra variables a and b, which are the lengths of the other two sides of the triangle. This enables us to express the given condition, which is that the triangle is rightangled, by the Pythagorean Theorem: h2 − a2 1 b2 The other connections among the variables come by writing expressions for the area and perimeter: 25 − 12 ab P − a 1 b 1 h Since P is given, notice that we now have three equations in the three unknowns a, b, and h: 1
h2 − a2 1 b2
2
25 − 12 ab
3
PS Relate to the familiar.
P−a1b1h
Although we have the correct number of equations, they are not easy to solve in a straightforward fashion. But if we use the problemsolving strategy of trying to recognize something familiar, then we can solve these equations by an easier method. Look at the right sides of Equations 1, 2, and 3. Do these expressions remind you of anything familiar? Notice that they contain the ingredients of a familiar formula: sa 1 bd2 − a 2 1 2ab 1 b 2 Using this idea, we express sa 1 bd2 in two ways. From Equations 1 and 2 we have sa 1 bd2 − sa 2 1 b 2 d 1 2ab − h 2 1 4s25d − h 2 1 100 From Equation 3 we have sa 1 bd2 − sP 2 hd2 − P 2 2 2Ph 1 h 2 Thus
h 2 1 100 − P 2 2 2Ph 1 h 2 2Ph − P 2 2 100 h−
P 2 2 100 2P
This is the required expression for h as a function of P.
■
As the next example illustrates, it is often necessary to use the problemsolving prin ciple of taking cases when dealing with absolute values. 72 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
EXAMPLE 2 Solve the inequality  x 2 3  1  x 1 2  , 11. SOLUTION Recall the definition of absolute value:
x − It follows that
x 2 3 − − Similarly
x 1 2 − − PS Take cases.
H H H H
H
x if x > 0 2x if x , 0
x23 if x 2 3 > 0 2sx 2 3d if x 2 3 , 0 x23 2x 1 3
if x > 3 if x , 3
x12 if x 1 2 > 0 2sx 1 2d if x 1 2 , 0 x12 2x 2 2
if x > 22 if x , 22
These expressions show that we must consider three cases: x , 22 22 < x , 3 x > 3 CASE I If x , 22, we have
 x 2 3  1  x 1 2  , 11 2x 1 3 2 x 2 2 , 11 22x , 10 x . 25 CASE II If 22 < x , 3, the given inequality becomes
2x 1 3 1 x 1 2 , 11 5 , 11 (always true) CASE III If x > 3, the inequality becomes
x 2 3 1 x 1 2 , 11 2x , 12 x,6 Combining cases I, II, and III, we see that the inequality is satisfied when 25 , x , 6. So the solution is the interval s25, 6d. ■ In the following example we first guess the answer by looking at special cases and recognizing a pattern. Then we prove our conjecture by mathematical induction. In using the Principle of Mathematical Induction, we follow three steps: Step 1 Prove that Sn is true when n − 1. Step 2 Assume that Sn is true when n − k and deduce that Sn is true when n − k 1 1. Step 3 Conclude that Sn is true for all n by the Principle of Mathematical Induction. 73 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
EXAMPLE 3 If f0sxd − xysx 1 1d and fn11 − f0 8 fn for n − 0, 1, 2, . . . , find a formula
for fnsxd. PS Analogy: Try a similar, simpler
problem.
SOLUTION We start by finding formulas for fnsxd for the special cases n − 1, 2, and 3.
S D
x f1sxd − s f0 8 f0dsxd − f0( f0sxd) − f0 x11 x x x11 x11 x − − − x 2x 1 1 2x 1 1 11 x11 x11
S
D
S
D
x f2sxd − s f0 8 f1 dsxd − f0( f1sxd) − f0 2x 1 1 x x 2x 1 1 2x 1 1 x − − − x 3x 1 1 3x 1 1 11 2x 1 1 2x 1 1
x f3sxd − s f0 8 f2 dsxd − f0( f2sxd) − f0 3x 1 1 x x 3x 1 1 3x 1 1 x − − − x 4x 1 1 4x 1 1 11 3x 1 1 3x 1 1
PS Look for a pattern.
We notice a pattern: the coefficient of x in the denominator of fnsxd is n 1 1 in the three cases we have computed. So we make the guess that, in general, 4
fnsxd −
x sn 1 1dx 1 1
To prove this, we use the Principle of Mathematical Induction. We have already verified that (4) is true for n − 1. Assume that it is true for n − k, that is, fksxd − Then
x sk 1 1dx 1 1
S
x fk11sxd − s f0 8 fk dsxd − f0( fksxd) − f0 sk 1 1dx 1 1
D
x x sk 1 1dx 1 1 sk 1 1dx 1 1 x − − − x sk 1 2dx 1 1 sk 1 2dx 1 1 11 sk 1 1dx 1 1 sk 1 1dx 1 1
This expression shows that (4) is true for n − k 1 1. Therefore, by mathematical induction, it is true for all positive integers n. ■ 74 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Problems
1. One of the legs of a right triangle has length 4 cm. Express the length of the altitude perpendicular to the hypotenuse as a function of the length of the hypotenuse. 2. The altitude perpendicular to the hypotenuse of a right triangle is 12 cm. Express the length of the hypotenuse as a function of the perimeter.

 − 3. 4. Solve the inequality  x 2 1  2  x 2 3  > 5. 
3. Solve the equation 4x 2 x 1 1

   6. Sketch the graph of the function tsxd −  x 2 1  2  x 2 4 . 7. Draw the graph of the equation x 1  x  − y 1  y . 5. Sketch the graph of the function f sxd − x 2 2 4 x 1 3 . 2
2
8. Sketch the region in the plane consisting of all points sx, yd such that
x 2 y 1 x 2 y < 2 9. The notation maxha, b, . . .j means the largest of the numbers a, b, . . . . Sketch the graph of each function. (a) f sxd − maxhx, 1yxj (b) f sxd − maxhsin x, cos xj (c) f sxd − maxhx 2, 2 1 x, 2 2 xj 0. Sketch the region in the plane defined by each of the following equations or inequalities. 1 (a) maxhx, 2yj − 1 (b) 21 < maxhx, 2yj < 1 (c) maxhx, y 2 j − 1 11. Show that if x . 0 and x Þ 1, then 1 1 1 1 1 1 − log 2 x log 3 x log 5 x log 30 x 12. Find the number of solutions of the equation sin x −
x . 100
13. Find the exact value of sin
2 3 200 1 sin 1 sin 1 ∙ ∙ ∙ 1 sin 100 100 100 100
14. (a) Show that the function f sxd − ln ( x 1 sx 2 1 1 ) is an odd function. ( b) Find the inverse function of f. 15. Solve the inequality lnsx 2 2 2x 2 2d < 0. 16. U se indirect reasoning to prove that log 2 5 is an irrational number. 17. A driver sets out on a journey. For the first half of the distance she drives at the leisurely pace of 50 kmyh; she drives the second half at 100 kmyh. What is her average speed on this trip?
75 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
18. Is it true that f 8 s t 1 hd − f 8 t 1 f 8 h ? 19. P rove that if n is a positive integer, then 7 n 2 1 is divisible by 6. 20. P rove that 1 1 3 1 5 1 ∙ ∙ ∙ 1 s2n 2 1d − n 2. 21. I f f0sxd − x 2 and fn11sxd − f0s fnsxdd for n − 0, 1, 2, . . . , find a formula for fnsxd. 1 and fn11 − f0 8 fn for n − 0, 1, 2, . . . , find an expression for fnsxd and 22x use mathematical induction to prove it.
22. ( a) If f0sxd −
(b) Graph f0 , f1, f2 , f3 on the same screen and describe the effects of repeated composition. ;
76 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
We know that when an object is dropped from a height it falls faster and faster. Galileo discovered that the distance the object has fallen is proportional to the square of the time elapsed. Calculus enables us to calculate the precise speed of the object at any time. In Exercise 2.7.11 you are asked to determine the speed at which a cliff di er plunges into the ocean. Icealex / Shutterstock.com
2
Limits and Derivatives IN A PREVIEW OF CALCULUS (immediately preceding Chapter 1) we saw how the idea of a limit underlies the various branches of calculus. It is therefore appropriate to begin our study of calculus by investigating limits and their properties. The special type of limit that is used to find tangents and velocities gives rise to the central idea in differential calculus, the derivative.
77 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
78
CHAPTER 2 Limits and Derivatives
2.1 The Tangent and Velocity Problems In this section we see how limits arise when we attempt to find the tangent to a curve or the velocity of an object.
L
■ The Tangent Problem
(a) P
C
L
(b)
The word tangent is derived from the Latin word tangens, which means “touching.” We can think of a tangent to a curve as a line that touches the curve and follows the same direction as the curve at the point of contact. How can this idea be made precise? For a circle we could simply follow Euclid and say that a tangent is a line that intersects the circle once and only once, as in Figure 1(a). For more complicated curves this definition is inadequate. Figure l(b) shows a line that appears to be a tangent to the curve C at point P, but it intersects C twice. To be specific, let’s look at the problem of trying to find a tangent line to the parabola y − x 2 in the following example.
EXAMPLE 1 Find an equation of the tangent line to the parabola y − x 2 at the point Ps1, 1d.
FIGURE 1 y
Q {x, ≈} y=≈
L
P (1, 1) x
0
SOLUTION We will be able to find an equation of the tangent line as soon as we know its slope m. The difficulty is that we know only one point, P, on , whereas we need two points to compute the slope. But observe that we can compute an approximation to m by choosing a nearby point Qsx, x 2 d on the parabola (as in Figure 2) and computing the slope mPQ of the secant line PQ. (A secant line, from the Latin word secans, meaning cutting, is a line that cuts [intersects] a curve more than once.) We choose x ± 1 so that Q ± P. Then mPQ −
FIGURE 2
x2 2 1 x21
For instance, for the point Qs1.5, 2.25d we have mPQ − x
mPQ
2 1.5 1.1 1.01 1.001
3 2.5 2.1 2.01 2.001
x
mPQ
0 0.5 0.9 0.99 0.999
1 1.5 1.9 1.99 1.999
2.25 2 1 1.25 − − 2.5 1.5 2 1 0.5
The tables in the margin show the values of mPQ for several values of x close to 1. The closer Q is to P, the closer x is to 1 and, it appears from the tables, the closer mPQ is to 2. This suggests that the slope of the tangent line should be m − 2. We say that the slope of the tangent line is the limit of the slopes of the secant lines, and we express this symbolically by writing lim mPQ − m and lim
Q lP
xl1
x2 2 1 −2 x21
Assuming that the slope of the tangent line is indeed 2, we use the pointslope form of the equation of a line [ y 2 y1 − msx 2 x 1d, see Appendix B] to write the equation of the tangent line through s1, 1d as
y 2 1 − 2sx 2 1d or y − 2x 2 1
■
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SECTION 2.1 The Tangent and Velocity Problems
79
Figure 3 illustrates the limiting process that occurs in Example 1. As Q approaches P along the parabola, the corresponding secant lines rotate about P and approach the tangent line . y
Q
y
y
L
L
L
Q P
P
0
x
P x
0
Q x
0
Q approaches P from the right y
Q
y
L
P
Q x
0
y
L
P
L
Q
P x
x
0
Q approaches P from the left
FIGURE 3
Many functions that occur in the sciences are not described by explicit equations; they are defined by experimental data. The next example shows how to estimate the slope of the tangent line to the graph of such a function. t
Q
0 0.02 0.04 0.06 0.08 0.1
10 8.187 6.703 5.488 4.493 3.676
EXAMPLE 2 A pulse laser operates by storing charge on a capacitor and releasing it suddenly when the laser is fired. The data in the table describe the charge Q remaining on the capacitor (measured in coulombs) at time t (measured in seconds after the laser is fired). Use the data to draw the graph of this function and estimate the slope of the tangent line at the point where t − 0.04. (Note: The slope of the tangent line represents the electric current flowing from the capacitor to the laser [measured in amperes].) SOLUTION In Figure 4 we plot the given data and use these points to sketch a curve that approximates the graph of the function. Q (coulombs)
10 8 6 4
FIGURE 4
0
0.02
0.04
0.06
0.08
0.1
t (seconds)
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80
CHAPTER 2 Limits and Derivatives
Given the points Ps0.04, 6.703d and Rs0, 10d on the graph, we find that the slope of the secant line PR is mPR −
R
mPR
(0, 10) (0.02, 8.187) (0.06, 5.488) (0.08, 4.493) (0.1, 3.676)
282.425 274.200 260.750 255.250 250.450
10 2 6.703 − 282.425 0 2 0.04
The table at the left shows the results of similar calculations for the slopes of other secant lines. From this table we would expect the slope of the tangent line at t − 0.04 to lie somewhere between 274.20 and 260.75. In fact, the average of the slopes of the two closest secant lines is 1 2 s274.20
2 60.75d − 267.475
So, by this method, we estimate the slope of the tangent line to be about 267.5. Another method is to draw an approximation to the tangent line at P and measure the sides of the triangle ABC, as in Figure 5. Q (coulombs)
10 9 8
A P
7 6 5
FIGURE 5 The physical meaning of the answer in Example 2 is that the electric current flowing from the capacitor to the laser after 0.04 seconds is about 265 amperes.
0
B
C
0.02
0.04
0.06
0.08
0.1
t (seconds)
This gives an estimate of the slope of the tangent line as
2
 AB  < 2 8.0 2 5.4 − 265.0 0.06 2 0.02  BC 
■
■ The Velocity Problem If you watch the speedometer of a car as you drive in city traffic, you see that the speed doesn’t stay the same for very long; that is, the velocity of the car is not constant. We assume from watching the speedometer that the car has a definite velocity at each moment, but how is the “instantaneous” velocity defined? Let’s consider the velocity problem: Find the instantaneous velocity of an object moving along a straight path at a specific time if the position of the object at any time is known. In the next example, we investigate the velocity of a falling ball. Through experiments carried out four centuries ago, Galileo discovered that the distance fallen by any freely falling body is proportional to the square of the time it has been falling. (This model for free fall neglects air resistance.) If the distance fallen after t seconds is denoted by sstd and measured in meters, then (at the earth’s surface) Galileo’s observation is expressed by the equation sstd − 4.9t 2
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SECTION 2.1 The Tangent and Velocity Problems
81
EXAMPLE 3 Suppose that a ball is dropped from the upper observation deck of the CN Tower in Toronto, 450 m above the ground. Find the velocity of the ball after 5 seconds. SOLUTION The difficulty in finding the instantaneous velocity at 5 seconds is that we are dealing with a single instant of time st − 5d, so no time interval is involved. However, we can approximate the desired quantity by computing the average velocity over the brief time interval of a tenth of a second from t − 5 to t − 5.1:
Steve Allen / Stockbyte / Getty Images
average velocity −
change in position time elapsed
−
ss5.1d 2 ss5d 0.1
−
4.9s5.1d2 2 4.9s5d2 − 49.49 mys 0.1
The following table shows the results of similar calculations of the average velocity over successively smaller time periods.
CN Tower in Toronto
Time interval
s
s=4.9t @ Q
5
0
5+h
5 < t < 5.1
49.49
5 < t < 5.05
49.245
5 < t < 5.01 5 < t < 5.001
49.049 49.0049
It appears that as we shorten the time period, the average velocity is becoming closer to 49 mys. The instantaneous velocity when t − 5 is defined to be the limiting value of these average velocities over shorter and shorter time periods that start at t − 5. Thus it appears that the (instantaneous) velocity after 5 seconds is 49 mys. ■
slope of secant line average velocity
P
t
s
s=4.9t @
You may have the feeling that the calculations used in solving this problem are very similar to those used earlier in this section to find tangents. In fact, there is a close connection between the tangent problem and the velocity problem. If we draw the graph of the distance function of the ball (as in Figure 6) and we consider the points Ps5, 4.9s5d 2 d and Qs5 1 h, 4.9s5 1 hd2 d on the graph, then the slope of the secant line PQ is mPQ −
slope of tangent line instantaneous velocity
P 0
5
FIGURE 6
Average velocity smysd
t
4.9s5 1 hd2 2 4.9s5d 2 s5 1 hd 2 5
which is the same as the average velocity over the time interval f5, 5 1 hg. Therefore the velocity at time t − 5 (the limit of these average velocities as h approaches 0) must be equal to the slope of the tangent line at P (the limit of the slopes of the secant lines). Examples 1 and 3 show that in order to solve tangent and velocity problems we must be able to find limits. After studying methods for computing limits in the next five sections, we will return to the problems of finding tangents and velocities in Section 2.7.
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82
CHAPTER 2 Limits and Derivatives
2.1 Exercises 1. A tank holds 1000 liters of water, which drains from the bottom of the tank in half an hour. The values in the table show the volume V of water remaining in the tank (in liters) after t minutes. t smind V sLd
5
10
15
20
25
30
694
444
250
111
28
0
(a) If P is the point s15, 250d on the graph of V, find the slopes of the secant lines PQ when Q is the point on the graph with t − 5, 10, 20, 25, and 30. (b) Estimate the slope of the tangent line at P by averaging the slopes of two secant lines. (c) Use a graph of V to estimate the slope of the tangent line at P. (This slope represents the rate at which the water is flowing from the tank after 15 minutes.)
5. The deck of a bridge is suspended 80 meters above a river. If a pebble falls off the side of the bridge, the height, in meters, of the pebble above the water surface after t seconds is given by y − 80 2 4.9t 2. (a) Find the average velocity of the pebble for the time period beginning when t − 4 and lasting (i) 0.1 seconds (ii) 0.05 seconds (iii) 0.01 seconds (b) Estimate the instantaneous velocity of the pebble after 4 seconds. 6. If a rock is thrown upward on the planet Mars with a velocity of 10 mys, its height in meters t seconds later is given by y − 10 t 2 1.86t 2. (a) Find the average velocity over the given time intervals: (i) [1, 2] (ii) [1, 1.5] (iii) [1, 1.1] (iv) [1, 1.01] (v) [1, 1.001] (b) Estimate the instantaneous velocity when t − 1.
2. A student bought a smartwatch that tracks the number of steps she walks throughout the day. The table shows the number of steps recorded t minutes after 3:00 pm on the first day she wore the watch.
t smind
0
10
20
30
40
Steps
3438
4559
5622
6536
7398
(a) Find the slopes of the secant lines corresponding to the given intervals of t. What do these slopes represent? (i) [0, 40] (ii) [10, 20] (iii) [20, 30] (b) Estimate the student’s walking pace, in steps per minute, at 3:20 pm by averaging the slopes of two secant lines.
3. The point Ps2, 21d lies on the curve y − 1ys1 2 xd. (a) If Q is the point sx, 1ys1 2 xdd, find the slope of the secant line PQ (correct to six decimal places) for the following values of x : (i) 1.5 (ii) 1.9 (iii) 1.99 (iv) 1.999 (v) 2.5 (vi) 2.1 (vii) 2.01 (viii) 2.001 (b) Using the results of part (a), guess the value of the slope of the tangent line to the curve at Ps2, 21d. (c) Using the slope from part (b), find an equation of the tangent line to the curve at Ps2, 21d.
7. The table shows the position of a motorcyclist after acceler ating from rest. t ssecondsd
0
1
s (meters)
0
1.5
2
3
4
5
6.3 14.2 24.1 38.0
6 53.9
(a) Find the average velocity for each time period: (i) f2, 4g (ii) f3, 4g (iii) f4, 5g (iv) f4, 6g (b) Use the graph of s as a function of t to estimate the instantaneous velocity when t − 3. 8. The displacement (in centimeters) of a particle moving back and forth along a straight line is given by the equation of motion s − 2 sin t 1 3 cos t, where t is measured in seconds. (a) Find the average velocity during each time period: (i) f1, 2g (ii) f1, 1.1g (iii) f1, 1.01g (iv) f1, 1.001g (b) Estimate the instantaneous velocity of the particle when t − 1.
4. The point Ps0.5, 0d lies on the curve y − cos x . (a) If Q is the point s x, cos xd, find the slope of the secant line PQ (correct to six decimal places) for the following values of x : (i) 0 (ii) 0.4 (iii) 0.49 (iv) 0.499 (v) 1 (vi) 0.6 (vii) 0.51 (viii) 0.501 (b) Using the results of part (a), guess the value of the slope of the tangent line to the curve at Ps0.5, 0d.
(c) Using the slope from part (b), find an equation of the tangent line to the curve at Ps0.5, 0d. (d) Sketch the curve, two of the secant lines, and the tangent line.
9. The point Ps1, 0d lies on the curve y − sins10yxd. (a) If Q is the point sx, sins10yxdd, find the slope of the secant line PQ (correct to four decimal places) for x − 2, 1.5, 1.4, 1.3, 1.2, 1.1, 0.5, 0.6, 0.7, 0.8, and 0.9. Do the slopes appear to be approaching a limit? ; (b) Use a graph of the curve to explain why the slopes of the secant lines in part (a) are not close to the slope of the tangent line at P. (c) By choosing appropriate secant lines, estimate the slope of the tangent line at P.
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SECTION 2.2 The Limit of a Function
83
2.2 The Limit of a Function Having seen in the preceding section how limits arise when we want to find the tangent to a curve or the velocity of an object, we now turn our attention to limits in general and numerical and graphical methods for computing them.
■ Finding Limits Numerically and Graphically Let’s investigate the behavior of the function f defined by f sxd − sx 2 1dysx 2 2 1d for values of x near 1. The following table gives values of f sxd for values of x close to 1 but not equal to 1. x,1
f sxd
x.1
f sxd
0.5 0.9 0.99 0.999 0.9999
0.666667 0.526316 0.502513 0.500250 0.500025
1.5 1.1 1.01 1.001 1.0001
0.400000 0.476190 0.497512 0.499750 0.499975
1
0.5
1
0.5
y
y= ƒ approaches 0.5 0.5 0
x1 ≈1
1
x
From the table and the graph of f shown in Figure 1 we see that the closer x is to 1 (on either side of 1), the closer f sxd is to 0.5. In fact, it appears that we can make the values of f sxd as close as we like to 0.5 by taking x sufficiently close to 1. We express this by saying “the limit of the function f sxd − sx 2 1dysx 2 2 1d as x approaches 1 is equal to 0.5.” The notation for this is
as x approaches 1
lim
FIGURE 1
x l1
x21 − 0.5 x2 2 1
In general, we use the following notation. 1 Intuitive Definition of a Limi Suppose f sxd is defined when x is near the number a. (This means that f is defined on some open interval that contains a, except possibly at a itself.) Then we write lim f sxd − L
xla
and say
“the limit of f sxd, as x approaches a, equals L”
if we can make the values of f sxd arbitrarily close to L (as close to L as we like) by restricting x to be sufficiently close to a (on either side of a) but not equal to a. Roughly speaking, this says that the values of f sxd approach L as x approaches a. In other words, the values of f sxd tend to get closer and closer to the number L as x gets closer and closer to the number a (from either side of a) but x ± a. (A more precise definition will be given in Section 2.4.)
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84
CHAPTER 2 Limits and Derivatives
An alternative notation for lim f sxd − L
xla
f sxd l L as x l a
is
which is usually read “ f sxd approaches L as x approaches a.” Notice the phrase “but x not equal to a” in the definition of limit. This means that in finding the limit of f sxd as x approaches a, we never consider x − a. In fact, f sxd need not even be defined when x − a. The only thing that matters is how f is defined near a. Figure 2 shows the graphs of three functions. Note that in part (b), f sad is not defined and in part (c), f sad ± L. But in each case, regardless of what happens at a, it is true that lim x l a f sxd − L. y
y
y
L
L
L
0
a
0
x
a
0
x
(b)
(a)
a
x
(c)
FIGURE 2 lim f sxd − L in all three cases xla
EXAMPLE 1 Estimate the value of lim
tl0
st 2 1 9 2 3 . t2
SOLUTION The table lists values of the function for several values of t near 0.
t
st 2 1 9 2 3 t2
60.001 60.0001 60.00001 60.000001
0.166667 0.166670 0.167000 0.000000
t
st 2 1 9 2 3 t2
61.0
0.162277 . . .
60.5
0.165525 . . .
60.1
0.166620 . . .
60.05
0.166655 . . .
60.01
0.166666 . . .
As t approaches 0, the values of the function seem to approach 0.1666666 . . . and so we guess that 1 st 2 1 9 2 3 lim − ■ 2 tl0 t 6 In Example 1 what would have happened if we had taken even smaller values of t? The table in the margin shows the results from one calculator; you can see that something strange seems to be happening. If you try these calculations on your own calculator you might get different values, but eventually you will get the value 0 if you make t sufficiently small. Does this
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SECTION 2.2 The Limit of a Function
www.StewartCalculus.com For a further explanation of why calculators sometimes give false values, click on Lies My Calculator and Computer Told Me. In particular, see the section called The Perils of Subtraction.
85
mean that the answer is really 0 instead of 16 ? No, the value of the limit is 16 , as we will show in the next section. The problem is that the calculator gave false values because st 2 1 9 is very close to 3 when t is small. (In fact, when t is sufficiently small, a calculator’s value for st 2 1 9 is 3.000 . . . to as many digits as the calculator is capable of carrying.) Something similar happens when we try to graph the function f std −
st 2 1 9 2 3 t2
of Example 1 on a graphing calculator or computer. Parts (a) and (b) of Figure 3 show quite accurate graphs of f , and if we trace along the curve, we can estimate easily that the limit is about 16 . But if we zoom in too much, as in parts (c) and (d), then we get inaccurate graphs, again due to rounding errors within the calculations.
0.2
0.2
0.1
0.1
(a) _5¯t¯5
(b) _0.1¯t¯0.1
(c) _10 _6¯t¯10 _6
(d) _10 _7¯t¯10 _7
FIGURE 3
EXAMPLE 2 Guess the value of lim
xl0
x
sin x x
61.0 60.5 60.4 60.3 60.2 60.1 60.05 60.01 60.005 60.001
0.84147098 0.95885108 0.97354586 0.98506736 0.99334665 0.99833417 0.99958339 0.99998333 0.99999583 0.99999983
sin x . x
SOLUTION The function f sxd − ssin xdyx is not defined when x − 0. Using a calculator (and remembering that, if x [ R, sin x means the sine of the angle whose radian measure is x), we construct a table of values correct to eight decimal places. From the table at the left and the graph in Figure 4 we guess that lim
xl0
sin x −1 x
This guess is in fact correct, as will be proved in Chapter 3 using a geometric argument.
y
FIGURE 4
_1
1
y=
0
1
sin x x
x
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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86
CHAPTER 2 Limits and Derivatives
S
EXAMPLE 3 Find lim x 3 1 xl0
D
cos 5x . 10,000
SOLUTION As before, we construct a table of values. From the first table it appears that the limit might be zero. x3 1
x 1 0.5 0.1 0.05 0.01
cos 5x 10,000
x
1.000028 0.124920 0.001088 0.000222 0.000101
0.005 0.001
x3 1
cos 5x 10,000
0.00010009 0.00010000
But if we persevere with smaller values of x, the second table suggests that the limit is more likely to be 0.0001. In Section 2.5 we will be able to show that lim x l 0 cos 5x − 1 and that it follows that cos 5x 1 lim x 3 1 − − 0.0001 ■ xl0 10,000 10,000
S
D
■ OneSided Limits y
The Heaviside function H is defined by
1 0
FIGURE 5 The Heaviside function
Hstd − t
H
0 if t , 0 1 if t > 0
(This function is named after the electrical engineer Oliver Heaviside [1850 –1925] and can be used to describe an electric current that is switched on at time t − 0.) Its graph is shown in Figure 5. There is no single number that Hstd approaches as t approaches 0, so lim t l 0 Hstd does not exist. However, as t approaches 0 from the left, Hstd approaches 0. As t approaches 0 from the right, Hstd approaches 1. We indicate this situation symbolically by writing lim Hstd − 0 and lim1 Hstd − 1
t l 02
tl0
and we call these onesided limits. The notation t l 0 2 indicates that we consider only values of t that are less than 0. Likewise, t l 0 1 indicates that we consider only values of t that are greater than 0. 2 Intuitive Definition of neSided Limits We write lim f sxd − L
x la2
and say that the lefthand limit of f sxd as x approaches a [or the limit of f sxd as x approaches a from the left] is equal to L if we can make the values of f sxd arbitrarily close to L by restricting x to be sufficiently close to a with x less than a. We write lim1 f sxd − L x la
and say that the righthand limit of f sxd as x approaches a [or the limit of f sxd as x approaches a from the right] is equal to L if we can make the values of f sxd arbitrarily close to L by restricting x to be sufficiently close to a with x greater than a.
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87
SECTION 2.2 The Limit of a Function
For instance, the notation x l 52 means that we consider only x , 5, and x l 51 means that we consider only x . 5. Definition 2 is illustrated in Figure 6. y
y
L
ƒ x
0
x
a
a
0
x
x
(b) lim ƒ=L
(a) lim ƒ=L
FIGURE 6
ƒ
L
x a+
x a_
Notice that Definition 2 differs from Definition 1 only in that we require x to be less than (or greater than) a. By comparing these definitions, we see that the following is true. 3 lim f sxd − L if and only if lim2 f sxd − L and lim1 f sxd − L xla x la x la
EXAMPLE 4 The graph of a function t is shown in Figure 7. y 4 3
y=©
1 0
FIGURE 7
1
2
3
4
5
x
Use the graph to state the values (if they exist) of the following: (a) lim2 tsxd (b) lim1 tsxd (c) lim tsxd xl2
xl2
xl2
(d) lim2 tsxd (e) lim1 tsxd (f ) lim tsxd xl5
xl5
xl5
SOLUTION Looking at the graph we see that the values of tsxd approach 3 as x approaches 2 from the left, but they approach 1 as x approaches 2 from the right. Therefore (a) lim2 tsxd − 3 and (b) lim1 tsxd − 1 xl2
xl2
(c) Since the left and right limits are different, we conclude from (3) that lim x l 2 tsxd does not exist. The graph also shows that (d) lim2 tsxd − 2 and (e) lim1 tsxd − 2 xl5
xl5
(f ) This time the left and right limits are the same and so, by (3), we have lim tsxd − 2
xl5
Despite this fact, notice that ts5d ± 2. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
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88
CHAPTER 2 Limits and Derivatives
■ How Can a Limit Fail to Exist? We have seen that a limit fails to exist at a number a if the left and righthand limits are not equal (as in Example 4). The next two examples illustrate additional ways that a limit can fail to exist.
EXAMPLE 5 Investigate lim sin xl0
Limits and Technology Some software applications, including computer algebra systems (CAS), can compute limits. In order to avoid the types of pitfalls demonstrated in Examples 1, 3, and 5, such applications don’t find limits by numerical experimentation. Instead, they use more sophisticated techniques such as computing infinite series. You are encouraged to use one of these resources to compute the limits in the examples of this section and check your answers to the exercises in this chapter.
. x
SOLUTION Notice that the function f sxd − sinsyxd is undefined at 0. Evaluating the function for some small values of x, we get f s1d − sin − 0
f ( 12 ) − sin 2 − 0
f ( 13) − sin 3 − 0
f ( 14) − sin 4 − 0
f s0.1d − sin 10 − 0 f s0.01d − sin 100 − 0 Similarly, f s0.001d − f s0.0001d − 0. On the basis of this information we might be tempted to guess that the limit is 0, but this time our guess is wrong. Note that although f s1ynd − sin n − 0 for any integer n, it is also true that f sxd − 1 for infinitely many values of x (such as 2y5 or 2y101) that approach 0. You can see this from the graph of f shown in Figure 8. y
y=sin(π/x)
1
_1 1
x
_1
FIGURE 8
The dashed lines near the yaxis indicate that the values of sinsyxd oscillate between 1 and 21 infinitely often as x approaches 0. Since the values of f sxd do not approach a fixed number as x approaches 0,
lim sin
xl0
does not exist x
■
Examples 3 and 5 illustrate some of the pitfalls in guessing the value of a limit. It is easy to guess the wrong value if we use inappropriate values of x, but it is difficult to know when to stop calculating values. And, as the discussion after Example 1 shows, sometimes calculators and computers give the wrong values. In the next section, however, we will develop foolproof methods for calculating limits. Another way a limit at a number a can fail to exist is when the function values grow arbitrarily large (in absolute value) as x approaches a. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
89
SECTION 2.2 The Limit of a Function
EXAMPLE 6 Find lim
xl0
1 if it exists. x2
SOLUTION As x becomes close to 0, x 2 also becomes close to 0, and 1yx 2 becomes very large. (See the following table.) In fact, it appears from the graph of the function f sxd − 1yx 2 shown in Figure 9 that the values of f sxd can be made arbitrarily large by taking x close enough to 0. Thus the values of f sxd do not approach a number, so lim x l 0 s1yx 2 d does not exist.
x
1 x2
61 60.5 60.2 60.1 60.05 60.01 60.001
1 4 25 100 400 10,000 1,000,000
y
y= 1 ≈
0
x
FIGURE 9
■
■ Infinite Limits; Vertical Asymptotes To indicate the kind of behavior exhibited in Example 6, we use the notation lim
xl0
1 −` x2
This does not mean that we are regarding ` as a number. Nor does it mean that the limit exists. It simply expresses the particular way in which the limit does not exist: 1yx 2 can be made as large as we like by taking x close enough to 0. In general, we write symbolically lim f sxd − `
xla
to indicate that the values of f sxd tend to become larger and larger (or “increase without bound”) as x becomes closer and closer to a. 4 Intuitive Definition of an nfini e Limit Let f be a function defined on both sides of a, except possibly at a itself. Then lim f sxd − `
xla
means that the values of f sxd can be made arbitrarily large (as large as we please) by taking x sufficiently close to a, but not equal to a.
y
y=ƒ
Another notation for lim x l a f sxd − ` is f sxd l ` as x l a
0
a
x
x=a
FIGURE 10 lim f sxd − `
xla
Again, the symbol ` is not a number, but the expression lim x l a f sxd − ` is often read as “the limit of f sxd, as x approaches a, is infinity” or “ f sxd becomes infinite as x approaches a” or “ f sxd increases without bound as x approaches a” This definition is illustrated graphically in Figure 10.
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90
CHAPTER 2 Limits and Derivatives
A similar sort of limit, for functions that become large negative as x gets close to a, is defined in Definition 5 and is illustrated in Figure 11.
When we say a number is “large negative,” we mean that it is negative but its magnitude (absolute value) is large.
5 Definitio Let f be a function defined on both sides of a, except possibly at a itself. Then lim f sxd − 2`
y
x=a
xla
a
0
means that the values of f sxd can be made arbitrarily large negative by taking x sufficiently close to a, but not equal to a.
x
y=ƒ
The symbol lim x l a f sxd − 2` can be read as “the limit of f sxd, as x approaches a, is negative infinity” or “ f sxd decreases without bound as x approaches a.” As an example we have
FIGURE 11 lim f sxd − 2`
xla
S D
lim 2
xl0
1 x2
− 2`
Similar definitions can be given for the onesided infinite limits lim f sxd − `
lim f sxd − `
x l a2
x l a1
lim f sxd − 2`
lim f sxd − 2`
x l a2
x l a1
remembering that x l a2 means that we consider only values of x that are less than a, and similarly x l a1 means that we consider only x . a. Illustrations of these four cases are given in Figure 12. y
y
a
0
(a) lim ƒ=` x
a_
x
y
a
0
x
(b) lim ƒ=` x
a+
y
a
0
(c) lim ƒ=_` x
a
0
x
x
(d) lim ƒ=_`
a_
x
a+
FIGURE 12
6 Definitio The vertical line x − a is called a vertical asymptote of the curve y − f sxd if at least one of the following statements is true:
lim f sxd − `
x la
lim f sxd − 2`
x la
lim f sxd − `
x l a2
lim f sxd − 2`
x l a2
lim f sxd − `
x l a1
lim f sxd − 2`
x l a1
For instance, the yaxis is a vertical asymptote of the curve y − 1yx 2 because lim x l 0 s1yx 2 d − `. In Figure 12 the line x − a is a vertical asymptote in each of the four cases shown. In general, knowledge of vertical asymptotes is very useful in sketching graphs. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.2 The Limit of a Function
EXAMPLE 7 Does the curve y −
y
y=
91
2x have a vertical asymptote? x23
SOLUTION There is a potential vertical asymptote where the denominator is 0, that is, at x − 3, so we investigate the onesided limits there. If x is close to 3 but larger than 3, then the denominator x 2 3 is a small positive number and 2x is close to 6. So the quotient 2xysx 2 3d is a large positive number. [For instance, if x − 3.01 then 2xysx 2 3d − 6.02y0.01 − 602.] Thus, intuitively, we see that 2x lim1 −` x l3 x 2 3
2x x3
5
Likewise, if x is close to 3 but smaller than 3, then x 2 3 is a small negative number but 2x is still a positive number (close to 6). So 2xysx 2 3d is a numerically large negative number. Thus 2x lim − 2` x l 32 x 2 3
x
0
x=3
The graph of the curve y − 2xysx 2 3d is given in Figure 13. According to Definition 6, the line x − 3 is a vertical asymptote.
FIGURE 13
■
NOTE Neither of the limits in Examples 6 and 7 exist, but in Example 6 we can write lim x l 0 s1yx 2 d − ` because f sxd l ` as x approaches 0 from either the left or the right. In Example 7, f sxd l ` as x approaches 3 from the right but f sxd l 2` as x approaches 3 from the left, so we simply say that lim x l 3 f sxd does not exist. y
EXAMPLE 8 Find the vertical asymptotes of f sxd − tan x. SOLUTION Because tan x −
1 3π _π
_ 2
_
π 2
0
π 2
π
3π 2
x
there are potential vertical asymptotes where cos x − 0. In fact, since cos x l 01 as x l sy2d2 and cos x l 02 as x l sy2d1, whereas sin x is positive (near 1) when x is near y2, we have lim
FIGURE 14
x l sy2d2
y − tan x
y=ln x
1
x l sy2d1
tan x − 2`
■
1 x
Another example of a function whose graph has a vertical asymptote is the natural x Figure 15 we see that 0 logarithmic 1 function y − ln x. From
FIGURE 15
tan x − ` and lim
This shows that the line x − y2 is a vertical asymptote. Similar reasoning shows y the lines x − y2 1 n, where n is an integer, are all vertical asymptotes of that y=log f sxd − tan x. The graph Figure 14 confirms this. b x,inb>1
y
0
sin x cos x
The yaxis is (a) a vertical asymptote of the natural logarithmic function.
lim ln x − 2`
x l 01
and so the line(b)x − 0 (the yaxis) is a vertical asymptote. In fact, the same is true for y − log b x provided that b . 1. (See Figures 1.5.11 and 1.5.12.)
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92
CHAPTER 2 Limits and Derivatives
2.2 Exercises 1. Explain in your own words what is meant by the equation
( j) hs2d (k) lim1 hsxd (l) lim2 hsxd x l5
lim f sxd − 5
xl2
x l5
y
Is it possible for this statement to be true and yet f s2d − 3? Explain. 2. Explain what it means to say that lim f sxd − 3 and lim1 f sxd − 7
x l 12
x l1
In this situation is it possible that lim x l 1 f sxd exists? Explain.
_4
_2
0
2
4
x
6
3. Explain the meaning of each of the following. lim f sxd − ` (b) lim1 f sxd − 2` (a) x l 23
xl4
4. Use the given graph of f to state the value of each quantity, if it exists. If it does not exist, explain why. (a) lim2 f sxd (b) lim1 f sxd (c) lim f sxd x l2
xl2
xl2
(d) f s2d (e) lim f sxd
(f ) f s4d
xl4
7. F or the function t whose graph is shown, find a number a that satisfies the given description. (a) lim tsxd does not exist but tsad is defined. xla
lim tsxd exists but tsad is not defined. (b) xla
lim2 tsxd and lim1 tsxd both exist but lim tsxd does (c) xla
xla
xla
not exist. lim1 tsxd − tsad but lim2 tsxd Þ tsad . (d) xla
y
xla
y
4 2 0
2
4
0
x
2
4
6 x
5. For the function f whose graph is given, state the value of each quantity, if it exists. If it does not exist, explain why. (a) lim f sxd (b) lim2 f sxd (c) lim1 f sxd
8. For the function A whose graph is shown, state the following. (a) lim Asxd (b) lim2 Asxd
(d) lim f sxd (e) f s3d
lim1 Asxd (d) lim Asxd (c)
xl1
xl3
xl3
x l23
x l2
x l2
xl3
y
x l21
(e) The equations of the vertical asymptotes y
4 2 0
2
4
_3
x
6. For the function h whose graph is given, state the value of each quantity, if it exists. If it does not exist, explain why. (a) lim 2 hsxd (b) lim 1 hsxd (c) lim hsxd x l 23
x l 23
(d) hs23d (e) lim2 hsxd xl 0
x l 23
(f ) lim1 hsxd x l0
(g) lim hsxd (h) hs0d ( i) lim hsxd xl0
xl2
0
2
x
5
9. For the function f whose graph is shown, state the following. (a) lim f sxd (b) lim f sxd (c) lim f sxd x l27
x l23
xl0
(d) lim2 f sxd (e) lim1 f sxd xl6
xl6
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
93
SECTION 2.2 The Limit of a Function
(f ) The equations of the vertical asymptotes
17.
f sxd − 0, lim 1 f sxd − 1, lim f sxd − 3,
lim
x l 212
x l 21
xl2
f s21d − 2, f s2d − 1
y
18.
f sxd − 3, lim 1 f sxd − 2, lim2 f sxd − 21,
lim
x l 232
x l 23
xl3
lim1 f sxd − 2, f s23d − 2, f s3d − 0 xl3
_7
_3
0
6
x
19–22 Guess the value of the limit (if it exists) by evaluating the function at the given numbers (correct to six decimal places). 10. A patient receives a 150mg injection of a drug every 4 hours. The graph shows the amount f std of the drug in the bloodstream after t hours. Find lim f std and lim1 f std
t l 122
t l 12
and explain the significance of these onesided limits.
x 2 2 3x , x l3 x 2 2 9 x − 3.1, 3.05, 3.01, 3.001, 3.0001, 2.9, 2.95, 2.99, 2.999, 2.9999 19. lim
x 2 2 3x , x l 23 x 2 2 9 x − 22.5, 22.9, 22.95, 22.99, 22.999, 22.9999, 23.5, 23.1, 23.05, 23.01, 23.001, 23.0001
20. lim
f(t) 300
21. lim
tl0
s2 1 hd5 2 32 , hl 0 h h − 60.5, 60.1, 60.01, 60.001, 60.0001
22. lim
150
0
4
8
12
16
t
11–12 Sketch the graph of the function and use it to determine the values of a for which lim x l a f sxd exists.
H H
13. f sxd − x s1 1 x 22
ln x 2 ln 4 x24
24. lim
25. lim
sin 3 tan 2
26. lim
27. lim1
x x
28. lim1 x 2 ln x
x l0
xl0
14. f sxd −
t l0
5t 2 1 t
x l0
e1yx 2 2 e1yx 1 1
15–18 Sketch the graph of an example of a function f that satisfies all of the given conditions. 15. lim2 f sxd − 3, lim1 f sxd − 0, f s1d − 2
x11 x25
30. lim2
x11 x25
x2 sx 2 2d2
32. lim2
sx sx 2 3d 5
29. lim1 x l5
31. lim
x l2
33. lim1 ln (sx 2 1) x l1
35.
lim
xlsy2d1
1 sec x x
x l5
x l3
34. lim1 lnssin xd xl0
36. lim2 x cot x x l
2
2
x 1 2x x 2 2x 1 1
38. lim2
39. lim sln x 2 2 x22 d
40. lim1
37. lim
x l1
x l3
xl1
16. lim f sxd − 4, lim2 f sxd − 1, lim1 f sxd − 23, xl0
p l 21
29–40 Determine the infinite limit.
; 13–14 Use the graph of the function f to state the value of each limit, if it exists. If it does not exist, explain why. (a) lim2 f sxd (b) lim1 f sxd (c) lim f sxd xl0
xl8
f s0d − 6, f s8d − 21
xl8
1 1 p9 1 1 p 15
23. lim
l0
3 x if x < 21 s 12. f sxd − x if 21 , x < 2 sx 2 1d2 if x . 2
xl0
23–28 Use a table of values to estimate the value of the limit. If you have a graphing device, use it to confirm your result graphically. xl4
ex if x < 0 11. f sxd − x 2 1 if 0 , x , 1 if x > 1 ln x
xl1
e 5t 2 1 , t − 60.5, 60.1, 60.01, 60.001, 60.0001 t
xl0
xl0
x 2 1 4x x 2 2x 2 3
S
2
D
1 2 ln x x
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
94
CHAPTER 2 Limits and Derivatives
48. (a) Evaluate the function
41. Find the vertical asymptote of the function f sxd −
x21 2x 1 4
hsxd −
42. (a) Find the vertical asymptotes of the function y− ;
;
(b) Confirm your answer to part (a) by graphing the function. 1 1 and lim1 3 x l1 x 2 1 x3 2 1 (a) by evaluating f sxd − 1ysx 3 2 1d for values of x that approach 1 from the left and from the right, (b) by reasoning as in Example 7, and (c) from a graph of f. x l1
for x − 1, 0.5, 0.1, 0.05, 0.01, and 0.005.
x2 1 1 3x 2 2x 2
43. Determine lim2
;
; 44. (a) By graphing the function f sxd −


x ; 46. (a) Graph the function f sxd − e 1 ln x 2 4 for 0 < x < 5. Do you think the graph is an accurate representation of f ? (b) How would you get a graph that represents f better?
47. (a) Evaluate the function f sxd − x 2 2 s2 xy1000d for x − 1, 0.8, 0.6, 0.4, 0.2, 0.1, and 0.05, and guess the value of 2x lim x 2 2 xl0 1000
D
(b) Evaluate f sxd for x − 0.04, 0.02, 0.01, 0.005, 0.003, and 0.001. Guess again.
2 < x <
Then find the exact equations of these asymptotes. 50. Consider the function f sxd − tan
45. (a) Estimate the value of the limit lim x l 0 s1 1 xd1yx to five decimal places. Does this number look familiar? (b) Illustrate part (a) by graphing the function ; y − s1 1 xd1yx.
xl0
y − tans2 sin xd
and zooming in toward the point where the graph crosses the yaxis, estimate the value of lim x l 0 f sxd. (b) Check your answer in part (a) by evaluating f sxd for values of x that approach 0.
S
tan x 2 x . x3 (c) Evaluate hsxd for successively smaller values of x until you finally reach a value of 0 for hsxd. Are you still confident that your guess in part (b) is correct? Explain why you eventually obtained 0 values. (In Section 4.4 a method for evaluating this limit will be explained.) (d) Graph the function h in the viewing rectangle f21, 1g by f0, 1g. Then zoom in toward the point where the graph crosses the yaxis to estimate the limit of hsxd as x approaches 0. Continue to zoom in until you observe distortions in the graph of h. Compare with the results of part (c). (b) Guess the value of lim
se a graph to estimate the equations of all the vertical ; 49. U asymptotes of the curve
cos 2x 2 cos x x2
tan x 2 x x3
1 . x
(a) Show that f sxd − 0 for x −
1 1 1 , , ,... 2 3
(b) Show that f sxd − 1 for x −
4 4 4 , , ,... 5 9
(c) What can you conclude about lim1 tan
xl0
1 ? x
51. I n the theory of relativity, the mass of a particle with velocity v is m−
m0 s1 2 v 2yc 2
where m 0 is the mass of the particle at rest and c is the speed of light. What happens as v l c2?
2.3 Calculating Limits Using the Limit Laws ■ Properties of Limits In Section 2.2 we used calculators and graphs to guess the values of limits, but we saw that such methods don’t always lead to the correct answers. In this section we use the following properties of limits, called the Limit Laws, to calculate limits.
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SECTION 2.3 Calculating Limits Using the Limit Laws
95
Limit Laws Suppose that c is a constant and the limits lim f sxd and lim tsxd
xla
xla
exist. Then 1. lim f f sxd 1 tsxdg − lim f sxd 1 lim tsxd xla
xla
xla
2. lim f f sxd 2 tsxdg − lim f sxd 2 lim tsxd xla
xla
xla
3. lim fcf sxdg − c lim f sxd xla
xla
4. lim f f sxd tsxdg − lim f sxd ? lim tsxd xla
xla
lim f sxd
5. lim
xla
f sxd xla − tsxd lim tsxd xla
xla
if lim tsxd ± 0 xla
These five laws can be stated verbally as follows: Sum Law Difference Law Constant Multiple Law Product Law Quotient Law
1. The limit of a sum is the sum of the limits. 2. The limit of a difference is the difference of the limits. 3. The limit of a constant times a function is the constant times the limit of the function. 4. The limit of a product is the product of the limits. 5. The limit of a quotient is the quotient of the limits (provided that the limit of the denominator is not 0). It is easy to believe that these properties are true. For instance, if f sxd is close to L and tsxd is close to M, it is reasonable to conclude that f sxd 1 tsxd is close to L 1 M. This gives us an intuitive basis for believing that Law 1 is true. In Section 2.4 we give a precise definition of a limit and use it to prove this law. The proofs of the remaining laws are given in Appendix F.
y
EXAMPLE 1 Use the Limit Laws and the graphs of f and t in Figure 1 to evaluate the following limits, if they exist.
f 1
0
g
(a) lim f f sxd 1 5tsxdg (b) lim f f sxdtsxdg (c) lim 1
x
x l 22
xl1
xl2
f sxd tsxd
SOLUTION (a) From the graphs of f and t we see that lim f sxd − 1 and lim tsxd − 21
x l 22
FIGURE 1
x l 22
Therefore we have lim f f sxd 1 5tsxdg − lim f sxd 1 lim f5tsxdg (by Limit Law 1)
x l 22
x l 22
x l 22
− lim f sxd 1 5 lim tsxd (by Limit Law 3) x l 22
x l 22
− 1 1 5s21d − 24
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96
CHAPTER 2 Limits and Derivatives
(b) We see that lim x l 1 f sxd − 2. But lim x l 1 tsxd does not exist because the left and right limits are different: lim tsxd − 22 lim1 tsxd − 21
x l 12
xl1
So we can’t use Law 4 for the desired limit. But we can use Law 4 for the onesided limits: lim f f sxd tsxdg − lim2 f sxd lim2 tsxd − 2 s22d − 24
x l 12
x l1
x l1
lim f f sxd tsxdg − lim1 f sxd lim1 tsxd − 2 s21d − 22
x l 11
x l1
x l1
The left and right limits aren’t equal, so lim x l 1 f f sxd tsxdg does not exist. (c) The graphs show that lim f sxd < 1.4 and lim tsxd − 0
xl2
xl2
Because the limit of the denominator is 0, we can’t use Law 5. The given limit does not exist because the denominator approaches 0 while the numerator approaches a nonzero number.
■
If we use the Product Law repeatedly with tsxd − f sxd, we obtain the following law. Power Law
f x la
g
6. lim f f sxdg n − lim f sxd n where n is a positive integer x la
A similar property, which you are asked to prove in Exercise 2.5.69, holds for roots: Root Law
n n lim f sxd f sxd − s 7. lim s where n is a positive integer x la
x la
f sxd . 0.g fIf n is even, we assume that xlim la
In applying these seven limit laws, we need to use two special limits: 8. lim c − c xla
9. lim x − a xla
These limits are obvious from an intuitive point of view (state them in words or draw graphs of y − c and y − x), but proofs based on the precise definition are requested in Exercises 2.4.23–24. If we now put f sxd − x in Law 6 and use Law 9, we get a useful special limit for power functions. 10. lim x n − a n where n is a positive integer xla
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SECTION 2.3 Calculating Limits Using the Limit Laws
Newton and Limits Isaac Newton was born on Christmas Day in 1642, the year of Galileo’s death. When he entered Cambridge University in 1661 Newton didn’t know much mathematics, but he learned quickly by reading Euclid and Descartes and by attending the lectures of Isaac Barrow. Cambridge was closed because of the plague from 1665 to 1666, and Newton returned home to refle t on what he had learned. Those two years were amazingly productive for at that time he made four of his major discoveries: (1) his representation of functions as sums of infini e series, including the binomial theorem; (2) his work on differential and integral calculus; (3) his laws of motion and law of universal gravitation; and (4) his prism experiments on the nature of light and color. Because of a fear of controversy and criticism, he was reluctant to publish his discoveries and it wasn’t until 1687, at the urging of the astronomer Halley, that Newton published Principia Mathematica. In this work, the greatest scientific t eatise ever written, Newton set forth his version of calculus and used it to investigate mechanics, fluid dynamic , and wave motion, and to explain the motion of planets and comets. The beginnings of calculus are found in the calculations of areas and volumes by ancient Greek scholars such as Eudoxus and Archimedes. Although aspects of the idea of a limit are implicit in their “method of exhaustion,” Eudoxus and Archimedes never explicitly formulated the concept of a limit. Likewise, mathematicians such as Cavalieri, Fermat, and Barrow, the immediate precursors of Newton in the development of calculus, did not actually use limits. It was Isaac Newton who was the first o talk explicitly about limits. He explained that the main idea behind limits is that quantities “approach nearer than by any given difference.” Newton stated that the limit was the basic concept in calculus, but it was left to later mathematicians like Cauchy to clarify his ideas about limits.
97
If we put f sxd − x in Law 7 and use Law 9, we get a similar special limit for roots. (For square roots the proof is outlined in Exercise 2.4.37.) n n x −s a where n is a positive integer 11. lim s
xla
(If n is even, we assume that a . 0.)
EXAMPLE 2 Evaluate the following limits and justify each step. x 3 1 2x 2 2 1 lim (a) lim s2x 2 2 3x 1 4d (b) x l5 x l 22 5 2 3x SOLUTION (a) lim s2x 2 2 3x 1 4d − lim s2x 2 d 2 lim s3xd 1 lim 4 (by Laws 2 and 1) x l5
x l5
x l5
x l5
− 2 lim x 2 2 3 lim x 1 lim 4 (by 3)
− 2s5 2 d 2 3s5d 1 4
− 39
x l5
x l5
x l5
(by 10, 9, and 8)
(b) We start by using Law 5, but its use is fully justified only at the final stage when we see that the limits of the numerator and denominator exist and the limit of the denominator is not 0. lim sx 3 1 2x 2 2 1d
x 3 1 2x 2 2 1 lim − x l 22 5 2 3x
x l 22
−
x l 22
lim x 3 1 2 lim x 2 2 lim 1 x l 22 x l 22 lim 5 2 3 lim x
x l 22
−
(by Law 5)
lim s5 2 3xd
x l 22
x l 22
s22d3 1 2s22d2 2 1 5 2 3s22d
−2
1 11
(by 1, 2, and 3) (by 10, 9, and 8)
■
■ Evaluating Limits by Direct Substitution In Example 2(a) we determined that lim x l 5 f sxd − 39, where f sxd − 2x 2 2 3x 1 4. Notice that f s5d − 39; in other words, we would have gotten the correct result simply by substituting 5 for x. Similarly, direct substitution provides the correct answer in part (b). The functions in Example 2 are a polynomial and a rational function, respectively, and similar use of the Limit Laws proves that direct substitution always works for such functions (see Exercises 59 and 60). We state this fact as follows. Direct Substitution Property If f is a polynomial or a rational function and a is in the domain of f , then lim f sxd − f sad
x la
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98
CHAPTER 2 Limits and Derivatives
Functions that have the Direct Substitution Property are called continuous at a and will be studied in Section 2.5. However, not all limits can be evaluated initially by direct substitution, as the following examples show.
EXAMPLE 3 Find lim
xl1
x2 2 1 . x21
SOLUTION Let f sxd − sx 2 2 1dysx 2 1d. We can’t find the limit by substituting x − 1 because f s1d isn’t defined. Nor can we apply the Quotient Law, because the limit of the denominator is 0. Instead, we need to do some preliminary algebra. We factor the numerator as a difference of squares: x2 2 1 sx 2 1dsx 1 1d − x21 x21 Notice that in Example 3 we do not have an infinite limit even though the denominator approaches 0 as x l 1. When both numerator and denominator approach 0, the limit may be infinite or it may be some finite value.
The numerator and denominator have a common factor of x 2 1. When we take the limit as x approaches 1, we have x ± 1 and so x 2 1 ± 0. Therefore we can cancel the common factor, x 2 1, and then compute the limit by direct substitution as follows: lim
xl1
x2 2 1 sx 2 1dsx 1 1d − lim x l 1 x21 x21 − lim sx 1 1d − 1 1 1 − 2 xl1
The limit in this example arose in Example 2.1.1 in finding the tangent to the parabola y − x 2 at the point s1, 1d. ■
y
y=ƒ
3
NOTE In Example 3 we were able to compute the limit by replacing the given function f sxd − sx 2 2 1dysx 2 1d by a simpler function, tsxd − x 1 1, that has the same limit. This is valid because f sxd − tsxd except when x − 1, and in computing a limit as x approaches 1 we don’t consider what happens when x is actually equal to 1. In general, we have the following useful fact.
2
If f sxd − tsxd when x ± a, then lim f sxd − lim tsxd, provided the limits exist. x la
xla
1 0
1
2
3
x
EXAMPLE 4 Find lim tsxd where x l1
y
tsxd −
y=©
3 2 1 0
1
2
3
x
FIGURE 2 The graphs of the functions f (from Example 3) and t (from Example 4)
H
x 1 1 if x ± 1 if x − 1
SOLUTION Here t is defined at x − 1 and ts1d − , but the value of a limit as x approaches 1 does not depend on the value of the function at 1. Since tsxd − x 1 1 for x ± 1, we have
lim tsxd − lim sx 1 1d − 2
xl1
xl1
■
Note that the values of the functions in Examples 3 and 4 are identical except when x − 1 (see Figure 2) and so they have the same limit as x approaches 1.
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SECTION 2.3 Calculating Limits Using the Limit Laws
EXAMPLE 5 Evaluate lim
hl0
99
s3 1 hd2 2 9 . h
SOLUTION If we define Fshd −
s3 1 hd2 2 9 h
then, as in Example 3, we can’t compute lim h l 0 Fshd by letting h − 0 because Fs0d is undefined. But if we simplify Fshd algebraically, we find that Fshd −
−
s9 1 6h 1 h 2 d 2 9 6h 1 h 2 − h h hs6 1 hd −61h h
(Recall that we consider only h ± 0 when letting h approach 0.) Thus
lim
hl0
EXAMPLE 6 Find lim
tl0
s3 1 hd2 2 9 − lim s6 1 hd − 6 hl0 h
■
st 2 1 9 2 3 . t2
SOLUTION We can’t apply the Quotient Law immediately because the limit of the denominator is 0. Here the preliminary algebra consists of rationalizing the numerator: lim
tl0
st 2 1 9 2 3 st 2 1 9 2 3 st 2 1 9 1 3 − lim 2 t tl0 t2 st 2 1 9 1 3 − lim
st 2 1 9d 2 9 t 2 (st 2 1 9 1 3)
− lim
t2 t (st 2 1 9 1 3)
− lim
1 st 1 9 1 3
tl0
tl0
tl0
−
2
2
1 (Here we use several properties slim st 2 1 9d 1 3 of limits: 5, 1, 7, 8, 10.) t l0
−
1 1 − 313 6
This calculation confirms the guess that we made in Example 2.2.1.
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■
100
CHAPTER 2 Limits and Derivatives
■ Using OneSided Limits Some limits are best calculated by first finding the left and righthand limits. The following theorem is a reminder of what we discovered in Section 2.2. It says that a twosided limit exists if and only if both of the onesided limits exist and are equal. 1 Theorem lim f sxd − L if and only if lim2 f sxd − L − lim1 f sxd xla
x la
x la
When computing onesided limits, we use the fact that the Limit Laws also hold for onesided limits.
EXAMPLE 7 Show that lim  x  − 0. xl0
SOLUTION Recall that The result of Example 7 looks plausible from Figure 3. y
H
x −  
x if x > 0 2x if x , 0
Since x − x for x . 0, we have
 
lim x − lim1 x − 0
x l 01
y= x
 
x l0
For x , 0 we have x − 2x and so
 
lim x − lim2 s2xd − 0
x l 02
0
x
Therefore, by Theorem 1,
FIGURE 3
x l0
 
lim x − 0
xl0
EXAMPLE 8 Prove that lim
xl0
■
 x  does not exist. x
 
 
SOLUTION Using the facts that x − x when x . 0 and x − 2x when x , 0, we have
y=
y
x x
lim
x −
lim
x −
x l 01
1 0
FIGURE 4
_1
x l 02
x
x x
lim
x − lim1 1 − 1 x l0 x
lim
2x − lim2 s21d − 21 x l0 x
x l 01
x l 02
Since the right and lefthand limits are different, it follows from Theorem 1 that lim x l 0 x yx does not exist. The graph of the function f sxd − x yx is shown in Figure 4 and supports the onesided limits that we found.
 
 
EXAMPLE 9 If f sxd −
H
sx 2 4 8 2 2x
■
if x . 4 if x , 4
determine whether lim x l 4 f sxd exists.
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SECTION 2.3 Calculating Limits Using the Limit Laws
101
SOLUTION Since f sxd − sx 2 4 for x . 4, we have
It is shown in Example 2.4.4 that lim x l 01 sx − 0.
lim f sxd − lim1 s x 2 4 − s4 2 4 − 0
x l 41
x l4
Since f sxd − 8 2 2x for x , 4, we have
y
lim f sxd − lim2 s8 2 2xd − 8 2 2 ? 4 − 0
x l 42
x l4
The right and lefthand limits are equal. Thus the limit exists and 0
x
4
lim f sxd − 0
xl4
FIGURE 5
The graph of f is shown in Figure 5.
Other notations for v x b are fxg and
EXAMPLE 10 The greatest integer function is defined by v x b − the largest integer that is less than or equal to x. (For instance, v4 b − 4, v4.8b − 4, v b − 3, vs2 b − 1, v212 b − 21.) Show that lim x l3 v x b does not exist.
:x;. The greatest integer function is
sometimes called the floor function. y
SOLUTION The graph of the greatest integer function is shown in Figure 6. Since v x b − 3 for 3 < x , 4, we have
4 3
lim v x b − lim1 3 − 3
x l 31
y=[ x]
2
1
2
3
4
5
x l3
Since v x b − 2 for 2 < x , 3, we have
1 0
■
lim v x b − lim2 2 − 2
x l 32
x
x l3
Because these onesided limits are not equal, lim xl3 v x b does not exist by Theorem 1. ■
■ The Squeeze Theorem FIGURE 6
The following two theorems describe how the limits of functions are related when the values of one function are greater than (or equal to) those of another. Their proofs can be found in Appendix F.
Greatest integer function
2 Theorem If f sxd < tsxd when x is near a (except possibly at a) and the limits of f and t both exist as x approaches a, then lim f sxd < lim tsxd
xla
y
h g
L
f 0
FIGURE 7
a
x
xla
3 The Squeeze Theorem If f sxd < tsxd < hsxd when x is near a (except possibly at a) and lim f sxd − lim hsxd − L xla
then
xla
lim tsxd − L
xla
The Squeeze Theorem, which is sometimes called the Sandwich Theorem or the Pinching Theorem, is illustrated by Figure 7. It says that if tsxd is squeezed between f sxd and hsxd near a, and if f and h have the same limit L at a, then t is forced to have the same limit L at a.
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102
CHAPTER 2 Limits and Derivatives
EXAMPLE 11 Show that lim x 2 sin xl0
1 − 0. x
SOLUTION First note that we cannot rewrite the limit as the product of the limits lim x l 0 x 2 and lim x l 0 sins1yxd because lim x l 0 sins1yxd does not exist (see Example 2.2.5). We can find the limit by using the Squeeze Theorem. To apply the Squeeze Theorem we need to find a function f smaller than tsxd − x 2 sins1yxd and a function h bigger than t such that both f sxd and hsxd approach 0 as x l 0. To do this we use our knowledge of the sine function. Because the sine of any number lies between 21 and 1, we can write 4
1 0 for all x and so, multiplying each side of the inequalities in (4) by x 2, we get y
y=≈
1 < x2 x
2x 2 < x 2 sin as illustrated by Figure 8. We know that
lim x 2 − 0 and lim s2x 2 d − 0
x
0
y=_≈
FIGURE 8
xl0
xl0
Taking f sxd − 2x 2, tsxd − x 2 sins1yxd, and hsxd − x 2 in the Squeeze Theorem, we obtain
2
y − x sins1yxd
1 − 0 x
lim x 2 sin
xl0
■
2.3 Exercises x l2
lim f sxd − 4 lim tsxd − 22 lim hsxd − 0
xl2
xl 2
(a) lim f f sxd 1 5tsxdg (b) lim f tsxdg
(e) lim
x l2
(f ) lim
xl2
tsxd hsxd f sxd
2. The graphs of f and t are given. Use them to evaluate each limit, if it exists. If the limit does not exist, explain why. (a) lim f f sxd 1 tsxdg (b) lim f f sxd 2 tsxdg x l2
0
1 x
1
0
1
x
3–9 Evaluate the limit and justify each step by indicating the appropriate Limit Law(s). 3. lim s4x 2 2 5xd
4. lim s2x 3 1 6x 2 2 9d
5. lim sv 2 1 2vds2v 3 2 5d
6. lim
7. lim s9 2 u 3 1 2u 2
3 8. lim s x 1 5 s2x 2 2 3xd
x l5
xl 23
v l2
u l 22
xl0
f sxd (c) lim f f sxd tsxdg (d) lim x l 21 x l 3 tsxd
y=©
1
xl2
tsxd hsxd
y
y=ƒ
3
3f sxd (c) lim sf sxd (d) lim xl2 x l 2 tsxd
x l 21
y
xl2
find the limits that exist. If the limit does not exist, explain why. xl2
(f ) f s21d 1 lim tsxd
(e) lim fx 2 f sxdg
1. Given that
9. lim
tl 21
S
2t 5 2 t 4 5t 2 1 4
D
tl7
3t 2 1 1 t 2 2 5t 1 2
xl3
3
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103
SECTION 2.3 Calculating Limits Using the Limit Laws
; 36. (a) Use a graph of
10. (a) What is wrong with the following equation? x2 1 x 2 6 −x13 x22
f sxd −
(b) In view of part (a), explain why the equation lim
xl2
x2 1 x 2 6 − lim sx 1 3d xl2 x22
is correct.
t 2 2 2t 2 8 t24
14. lim
15. lim
x 2 1 5x 1 4 x22
16. lim
17. lim
x l 22
x l 23
x2 2 x 2 6 3x 2 1 5x 2 2
u11 u3 1 1
39. If 4x 2 9 < f sxd < x 2 2 4x 1 7 for x > 0, find lim f sxd.
92x
40. If 2x < tsxd < x 4 2 x 2 1 2 for all x, evaluate lim tsxd.
sh 2 3d 2 9 h
22. lim
s9 1 h 2 3 h
24. lim
u l 21
xl9
xl2
1 1 2 x 3 25. lim x l3 x 2 3
−0 x
20. lim
21. lim
hl0
lim sx 3 1 x 2 sin
xl0
2x 2 1 9x 2 5 x 2 2 25
x l 25
2
23. lim
; 38. Use the Squeeze Theorem to show that
x 2 1 3x x 2 x 2 12
18. lim
t 3 2 27 t2 2 9
hl 0
Illustrate by graphing the functions f sxd − 2x 2, tsxd − x 2 cos 20x, and hsxd − x 2 on the same screen.
x 2 1 3x x 2 x 2 12 2
2
xl4
19. lim
tl3
xl0
xl 6
13. lim
x l2
lim x 2 cos 20x − 0
12. lim (8 2 12 x)
xl 22
tl4
to estimate the value of lim x l 0 f sxd to two decimal places. (b) Use a table of values of f sxd to estimate the limit to four decimal places. (c) Use the Limit Laws to find the exact value of the limit.
; 37. Use the Squeeze Theorem to show that
11–34 Evaluate the limit, if it exists. 11. lim s3x 2 7d
s3 1 x 2 s3 x
26. lim
hl0
xl4
xl1
3 2 sx
2 41. Prove that lim x cos − 0. xl 0 x 4
22x sx 1 2 2 2
42. Prove that lim1 sx e sinsyxd − 0. xl 0
s22 1 hd21 1 2 21 h
S
Illustrate by graphing the functions f, t, and h (in the notation of the Squeeze Theorem) on the same screen.
D
43–48 Find the limit, if it exists. If the limit does not exist, explain why. 43. lim
( x 1 4  2 2x)
44. lim
2x 2 1 2x 3 2 x 2
46. lim
1 1 2 x x
48. lim1
 x 1 4
s1 1 t 2 s1 2 t 27. lim tl0 t
28. lim
4 2 sx 29. lim x l 16 16x 2 x 2
x 2 2 4x 1 4 30. lim 4 x l 2 x 2 3x 2 2 4
45. lim 2
sx 2 1 9 2 5 32. lim x l24 x14
47. lim2
1 1 2 2 sx 1 hd2 x 34. lim hl0 h
49. The Signum Function The signum (or sign) function, denoted by sgn, is defined by
31. lim
tl0
S
D
1
1 2 t t s1 1 t
sx 1 hd3 2 x 3 33. lim hl0 h ; 35. (a) Estimate the value of lim
x l0
tl0
1 1 2 2 t t 1t
x l 24
x l 0.5
xl 0

S

 D
x
by graphing the function f sxd − xyss1 1 3x 2 1d. (b) Make a table of values of f sxd for x close to 0 and guess the value of the limit. (c) Use the Limit Laws to prove that your guess is correct.
x l 22
sgn x −
s1 1 3x 2 1
x l 24
xl 0
H
2x 1 8
 
22 x 21x
S
1 1 2 x x
 
D
21 if x , 0 20 if x − 0 21 if x . 0
(a) Sketch the graph of this function. (b) Find each of the following limits or explain why it does not exist. (i) lim1 sgn x (ii) lim2 sgn x xl0
(iii) lim sgn x xl0
xl 0

(iv) lim sgn x xl 0

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104
CHAPTER 2 Limits and Derivatives
50. Let tsxd − sgnssin xd. (a) Find each of the following limits or explain why it does not exist. (i) lim1 tsxd (ii) lim2 tsxd (iii) lim tsxd xl0
xl0
(iv) lim1 tsxd
(v) lim2 tsxd
xl
xl0
(vi) lim tsxd
xl
xl
(b) For which values of a does lim x l a tsxd not exist? (c) Sketch a graph of t.
(ii) lim2 tsxd
x l2
xl1
(b) Does lim x l 2 tsxd exist? (c) Sketch the graph of t. f sxd −
61. If lim
x l2
52. Let
H
Bstd −
f sxd − 5, find the following limits. x2 f sxd (a) lim f sxd (b) lim xl0 xl0 x xl0
x2 1 1 if x , 1 sx 2 2d 2 if x > 1
H
63. If
4 2 12 t
if t , 2
st 1 c
if t > 2
f sxd −
x 3 tsxd − 2 2 x2 x23
65. S how by means of an example that lim x l a f f sxd tsxdg may exist even though neither lim x l a f sxd nor lim x l a tsxd exists.
x,1 x−1 1,x 21 for all x and so 2 1 cos x . 0 everywhere. Thus the ratio f sxd −
sin x 2 1 cos x
is continuous everywhere. Hence, by the definition of a continuous function,
lim
x l
sin x sin 0 − lim f sxd − f sd − − − 0 x l 2 1 cos x 2 1 cos 221
n
Another way of combining continuous functions f and t to get a new continuous function is to form the composite function f 8 t. This fact is a consequence of the following theorem. This theorem says that a limit symbol can be moved through a function symbol if the function is continuous and the limit exists. In other words, the order of these two symbols can be reversed.
8 Theorem If f is continuous at b and lim tsxd − b, then lim f stsxdd − f sbd. x la x la In other words, lim f stsxdd − f lim tsxd xla
xl a
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SECTION 2.5 Continuity
121
Intuitively, Theorem 8 is reasonable because if x is close to a, then tsxd is close to b, and since f is continuous at b, if tsxd is close to b, then fstsxdd is close to f sbd. A proof of Theorem 8 is given in Appendix F.
EXAMPLE 8 Evaluate lim arcsin x l1
S
D
1 2 sx . 12x
SOLUTION Because arcsin is a continuous function, we can apply Theorem 8: lim arcsin
x l1
S
1 2 sx 12x
D
S S S
D
− arcsin lim
1 2 sx 12x
− arcsin lim
1 2 sx (1 2 sx ) (1 1 sx )
− arcsin lim
1 1 1 sx
− arcsin
x l1
x l1
x l1
D
D
1 − 2 6
n
n Let’s now apply Theorem 8 in the special case where f sxd − s x , with n being a positive integer. Then n tsxd f stsxdd − s
and
f lim tsxd − xla
tsxd s xlim la n
If we put these expressions into Theorem 8, we get n n lim tsxd lim s tsxd − s
xla
xla
and so Limit Law 7 has now been proved. (We assume that the roots exist.) 9 Theorem If t is continuous at a and f is continuous at tsad, then the composite function f 8 t given by s f 8 tds xd − f stsxdd is continuous at a. This theorem is often expressed informally by saying “a continuous function of a continuous function is a continuous function.” PROOF Since t is continuous at a, we have lim tsxd − tsad
xla
Since f is continuous at b − tsad, we can apply Theorem 8 to obtain lim f stsxdd − f stsadd
xla
which is precisely the statement that the function hsxd − f s tsxdd is continuous at a; that is, f 8 t is continuous at a. Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
■
122
CHAPTER 2 Limits and Derivatives
EXAMPLE 9 Where are the following functions continuous? (a) hsxd − sinsx 2 d (b) Fsxd − lns1 1 cos xd
SOLUTION (a) We have hsxd − f s tsxdd, where
2
tsxd − x 2 and f sxd − sin x
_10
10
_6
FIGURE 7 y − lns1 1 cos xd
We know that t is continuous on R since it is a polynomial, and f is also continuous everywhere. Thus h − f 8 t is continuous on R by Theorem 9. (b) We know from Theorem 7 that f sxd − ln x is continuous and tsxd − 1 1 cos x is continuous (because both y − 1 and y − cos x are continuous). Therefore, by Theorem 9, Fsxd − f stsxdd is continuous wherever it is defined. The expression ln s1 1 cos xd is defined when 1 1 cos x . 0, so it is undefined when cos x − 21, and this happens when x − 6, 63, . . . . Thus F has discontinuities when x is an odd multiple of and is continuous on the intervals between these values (see Figure 7). n
■ The Intermediate Value Theorem An important property of continuous functions is expressed by the following theorem, whose proof is found in more advanced books on calculus. 10 The Intermediate Value Theorem Suppose that f is continuous on the closed interval fa, bg and let N be any number between f sad and f sbd, where f sad ± f sbd. Then there exists a number c in sa, bd such that f scd − N. The Intermediate Value Theorem states that a continuous function takes on every intermediate value between the function values f sad and f sbd. It is illustrated by Figure 8. Note that the value N can be taken on once [as in part (a)] or more than once [as in part (b)]. y
y
f(b)
f(b)
y=ƒ
N N
y=ƒ
f(a) 0
a
f(a)
y=N
f(b) a
FIGURE 9
x
0
a c¡
c™
c£
b
x
(b)
FIGURE 8
y=ƒ
N
0
c b
(a)
y
f(a)
b
x
If we think of a continuous function as a function whose graph has no hole or break, then it is easy to believe that the Intermediate Value Theorem is true. In geometric terms it says that if any horizontal line y − N is given between y − f sad and y − f sbd as in Figure 9, then the graph of f can’t jump over the line. It must intersect y − N somewhere. It is important that the function f in Theorem 10 be continuous. The Intermediate Value Theorem is not true in general for discontinuous functions (see Exercise 52).
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.5 Continuity
123
One use of the Intermediate Value Theorem is in locating solutions of equations as in the following example.
EXAMPLE 10 Show that there is a solution of the equation 4x 3 2 6x 2 1 3x 2 2 − 0 between 1 and 2. SOLUTION Let f sxd − 4x 3 2 6x 2 1 3x 2 2. We are looking for a solution of the given equation, that is, a number c between 1 and 2 such that f scd − 0. Therefore we take a − 1, b − 2, and N − 0 in Theorem 10. We have f s1d − 4 2 6 1 3 2 2 − 21 , 0 f s2d − 32 2 24 1 6 2 2 − 12 . 0
and
Thus f s1d , 0 , f s2d; that is, N − 0 is a number between f s1d and f s2d. The function f is continuous since it is a polynomial, so the Intermediate Value Theorem says there is a number c between 1 and 2 such that f scd − 0. In other words, the equation 4x 3 2 6x 2 1 3x 2 2 − 0 has at least one solution c in the interval s1, 2d. In fact, we can locate a solution more precisely by using the Intermediate Value Theorem again. Since f s1.2d − 20.128 , 0 and f s1.3d − 0.548 . 0 a solution must lie between 1.2 and 1.3. A calculator gives, by trial and error, f s1.22d − 20.007008 , 0 and f s1.23d − 0.056068 . 0 so a solution lies in the interval s1.22, 1.23d.
n
We can use a graphing calculator or computer to illustrate the use of the Intermediate Value Theorem in Example 10. Figure 10 shows the graph of f in the viewing rectangle f21, 3g by f23, 3g and you can see that the graph crosses the xaxis between 1 and 2. Figure 11 shows the result of zooming in to the viewing rectangle f1.2, 1.3g by f20.2, 0.2g. 3
0.2
3
_1
_3
FIGURE 10
1.2
1.3
_0.2
FIGURE 11
In fact, the Intermediate Value Theorem plays a role in the very way these graphing devices work. A computer calculates a finite number of points on the graph and turns on the pixels that contain these calculated points. It assumes that the function is continuous and takes on all the intermediate values between two consecutive points. The computer therefore “connects the dots” by turning on the intermediate pixels.
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124
CHAPTER 2 Limits and Derivatives
2.5 Exercises 1. Write an equation that expresses the fact that a function f is continuous at the number 4.
9. Discontinuities at 0 and 3, but continuous from the right at 0 and from the left at 3
2. If f is continuous on s2`, `d, what can you say about its graph?
10. C ontinuous only from the left at 21, not continuous from the left or right at 3
3. (a) From the given graph of f , state the numbers at which f is discontinuous and explain why. (b) For each of the numbers stated in part (a), determine whether f is continuous from the right, or from the left, or neither. y
_4
_2
0
2
4
12. Explain why each function is continuous or discontinuous. (a) The temperature at a specific location as a function of time (b) The temperature at a specific time as a function of the distance due west from New York City (c) The altitude above sea level as a function of the distance due west from New York City (d) The cost of a taxi ride as a function of the distance traveled (e) The current in the circuit for the lights in a room as a function of time
x
6
11. The toll T charged for driving on a certain stretch of a toll road is $5 except during rush hours (between 7 am and 10 am and between 4 pm and 7 pm) when the toll is $7. (a) Sketch a graph of T as a function of the time t, measured in hours past midnight. (b) Discuss the discontinuities of this function and their significance to someone who uses the road.
4. From the given graph of t, state the numbers at which t is discontinuous and explain why. y
13–16 Use the definition of continuity and the properties of limits to show that the function is continuous at the given number a. 13. f sxd − 3x 2 1 sx 1 2d5, a − 21 _3
_2
0
1
2
3
x
14. t std −
t 2 1 5t , a − 2 2t 1 1
15. psvd − 2s3v 2 1 1 , a − 1 3 4r 2 2 2r 1 7 , a − 22 16. f srd − s
5– 6 The graph of a function f is given. (a) At what numbers a does lim x l a f sxd not exist? (b) At what numbers a is f not continuous? (c) At what numbers a does lim x l a f sxd exist but f is not continuous at a ? 5.
y
6.
17 –18 Use the definition of continuity and the properties of limits to show that the function is continuous on the given interval. 17. f sxd − x 1 sx 2 4 , f4, `d
y
18. tsxd −
0
1
x
0
1
7 – 10 Sketch the graph of a function f that is defined on R and continuous except for the stated discontinuities. 7. Removable discontinuity at 22, infinite discontinuity at 2 8. Jump discontinuity at 23, removable discontinuity at 4
x
x21 , s2`, 22d 3x 1 6
19– 24 Explain why the function is discontinuous at the given number a. Sketch the graph of the function. 19. f sxd −
20. f sxd −
1 x12
H
1 x12 1
a − 22 if x ± 22 if x − 22
a − 22
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SECTION 2.5 Continuity
21. f sxd −
H
H H H
x 1 3 if x < 21 2x if x . 21
x2 2 x 22. f sxd − x 2 2 1 1
a − 21
a−1
cos x if x , 0 23. f sxd − 0 if x − 0 1 2 x 2 if x . 0 2x 2 2 5x 2 3 24. f sxd − x23 6
a−0
if x ± 3 if x − 3
a−3
25 –26 (a) Show that f has a removable discontinuity at x − 3. (b) Redefine f s3d so that f is continuous at x − 3 (and thus the discontinuity is “removed”). x23 x2 2 9
25. f sxd −
2
x 2 7x 1 12 x23
26. f sxd −
27 – 34 Explain, using Theorems 4, 5, 7, and 9, why the function is continuous at every number in its domain. State the domain. x2
27. f sxd −
29. hstd −
sx 4 1 2
28. tsvd −
3v 2 1 2 v 1 2v 2 15
cosst 2d 1 2 et
33. Msxd −
Î
11
1 x
2
32. f std − e2t lns1 1 t 2 d 34. tstd − cos21se t 2 1d
x l2
x l1
5 2 x2 11x
1 s1 2 sin x
43– 45 Find the numbers at which f is discontinuous. At which of these numbers is f continuous from the right, from the left, or neither? Sketch the graph of f .
H H H
x 2 if x , 21 43. f sxd − x if 21 < x , 1 1yx if x > 1 2x if x < 1 44. f sxd − 3 2 x if 1 , x < 4 if x . 4 sx x 1 2 if x , 0 45. f sxd − e x if 0 < x < 1 2 2 x if x . 1 46. T he gravitational force exerted by the planet Earth on a unit mass at a distance r from the center of the planet is
Fsrd −
38. lim 3 sx
2
22x24
xl4
GMr if r , R R3 GM if r > R r2
47. F or what value of the constant c is the function f continuous on s2`, `d? f sxd −
l y2
; 39 –40 Locate the discontinuities of the function and illustrate by graphing. 39. f sxd −
sin x if x , y4 cos x if x > y4
36. lim sinstanscos dd
S D
37. lim ln
1 2 x 2 if x < 1 ln x if x . 1
H
cx 2 1 2x if x , 2 x 3 2 cx if x > 2
48. Find the values of a and b that make f continuous everywhere.
35 – 38 Use continuity to evaluate the limit. 35. lim x s20 2 x 2
42. f sxd −
H H
where M is the mass of Earth, R is its radius, and G is the gravitational constant. Is F a continuous function of r ?
3 30. Bsud − s3u 2 2 1 s 2u 2 3
31. Lsvd − v lns1 2 v 2 d
41 – 42 Show that f is continuous on s2`, `d. 41. f sxd −
if x ± 1 if x − 1
125
40. y − arctan
1 x
f sxd −
x2 2 4 if x , 2 x22 ax 2 2 bx 1 3 if 2 < x , 3 2x 2 a 1 b if x > 3
49. S uppose f and t are continuous functions such that ts2d − 6 and lim x l 2 f3 f sxd 1 f sxd tsxdg − 36. Find f s2d. 50. Let f sxd − 1yx and tsxd − 1yx 2. (a) Find s f + tds xd. (b) Is f + t continuous everywhere? Explain.
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126
CHAPTER 2 Limits and Derivatives
51. W hich of the following functions f has a removable discon tinuity at a? If the discontinuity is removable, find a function t that agrees with f for x ± a and is continuous at a. (a) f sxd −
x4 2 1 , a − 1 x21
(b) f sxd −
x 3 2 x 2 2 2x , a − 2 x22
(c) f sxd − v sin x b , a − 52. S uppose that a function f is continuous on [0, 1] except at 0.25 and that f s0d − 1 and f s1d − 3. Let N − 2. Sketch two possible graphs of f , one showing that f might not satisfy the conclusion of the Intermediate Value Theorem and one showing that f might still satisfy the conclusion of the Intermediate Value Theorem (even though it doesn’t satisfy the hypothesis). 53. If f sxd − x 2 1 10 sin x, show that there is a number c such that f scd − 1000. 54. S uppose f is continuous on f1, 5g and the only solutions of the equation f sxd − 6 are x − 1 and x − 4. If f s2d − 8, explain why f s3d . 6. 55– 58 Use the Intermediate Value Theorem to show that there is a solution of the given equation in the specified interval.
66. T o prove that sine is continuous, we need to show that lim x l a sin x − sin a for every real number a. By Exercise 65 an equivalent statement is that lim sinsa 1 hd − sin a
hl0
Use (6) to show that this is true. 67. Prove that cosine is a continuous function. 68. (a) Prove Theorem 4, part 3. (b) Prove Theorem 4, part 5. 69. Use Theorem 8 to prove Limit Laws 6 and 7 from Section 2.3. 70. Is there a number that is exactly 1 more than its cube? 71. For what values of x is f continuous? f sxd −
56. ln x − x 2 sx , s2, 3d 57. e x − 3 2 2x, s0, 1d
58. sin x − x 2 2 x, s1, 2d
59 – 60 (a) Prove that the equation has at least one real solution. (b) Use a calculator to find an interval of length 0.01 that contains a solution. 59. cos x − x 3
60. ln x − 3 2 2x
; 61– 62 (a) Prove that the equation has at least one real solution. (b) Find the solution correct to three decimal places, by graphing. 61. 100e2xy100 − 0.01x 2
62. arctan x − 1 2 x
63– 64 Prove, without graphing, that the graph of the function has at least two xintercepts in the specified interval. 63. y − sin x 3, s1, 2d
64. y − x 2 2 3 1 1yx, s0, 2d
65. Prove that f is continuous at a if and only if lim f sa 1 hd − f sad
hl0
0 if x is rational 1 if x is irrational
72. For what values of x is t continuous? tsxd −
H
0 if x is rational x if x is irrational
73. Show that the function
3
55. 2x 1 4x 1 1 − 0, s21, 0d
H
f sxd −
H
x 4 sins1yxd 0
if x ± 0 if x − 0
is continuous on s2`, `d. 74. If a and b are positive numbers, prove that the equation a b 1 3 −0 x 3 1 2x 2 2 1 x 1x22 has at least one solution in the interval s21, 1d. 75. A woman leaves her house at 7:00 am and takes her usual path to the top of a mountain, arriving at 7:00 pm. The following morning, she starts at 7:00 am at the top and takes the same path back, arriving at her home at 7:00 pm. Use the Intermediate Value Theorem to show that there is a point on the path that the woman will cross at exactly the same time of day on both days. 76. Absolute Value and Continuity (a) Show that the absolute value function Fsxd − x is continuous everywhere. (b) Prove that if f is a continuous function on an interval, then so is f . (c) Is the converse of the statement in part (b) also true? In other words, if f is continuous, does it follow that f is continuous? If so, prove it. If not, find a counterexample.
 
 
 
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127
SECTION 2.6 Limits at Infini y; Horizontal Asymptotes
2.6 Limits at Infinity; Horizontal Asymptotes In Sections 2.2 and 2.4 we investigated infinite limits and vertical asymptotes of a curve y − f sxd. There we let x approach a number and the result was that the values of y became arbitrarily large (positive or negative). In this section we let x become arbitrarily large ( positive or negative) and see what happens to y.
■ Limits at Infinity and Horizontal Asymptotes Let’s begin by investigating the behavior of the function f defined by
x 0 61 62 63 64 65 610 650 6100 61000
f sxd −
f sxd 21 0 0.600000 0.800000 0.882353 0.923077 0.980198 0.999200 0.999800 0.999998
x2 2 1 x2 1 1
as x becomes large. The table at the left gives values of this function correct to six decimal places, and the graph of f has been drawn by a computer in Figure 1. y
0
y=1
1
y=
FIGURE 1
≈1 ≈+1
x
You can see that as x grows larger and larger, the values of f sxd get closer and closer to 1. (The graph of f approaches the horizontal line y − 1 as we look to the right.) In fact, it seems that we can make the values of f sxd as close as we like to 1 by taking x sufficiently large. This situation is expressed symbolically by writing lim
xl`
x2 2 1 −1 x2 1 1
In general, we use the notation lim f sxd − L
xl`
to indicate that the values of f sxd approach L as x becomes larger and larger. 1 Intuitive Definition of a Limit t Infini y Let f be a function defined on some interval sa, `d. Then lim f sxd − L
xl`
means that the values of f sxd can be made arbitrarily close to L by requiring x to be sufficiently large.
Another notation for lim x l ` f sxd − L is f sxd l L as x l `
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
128
CHAPTER 2 Limits and Derivatives
The symbol ` does not represent a number. Nonetheless, the expression lim f sxd − L is x l` often read as “the limit of f sxd, as x approaches infinity, is L” or
“the limit of f sxd, as x becomes infinite, is L”
or
“the limit of f sxd, as x increases without bound, is L”
The meaning of such phrases is given by Definition 1. A more precise definition, similar to the «, definition of Section 2.4, is given at the end of this section. Geometric illustrations of Definition 1 are shown in Figure 2. Notice that there are many ways for the graph of f to approach the line y − L (which is called a horizontal asymptote) as we look to the far right of each graph. y
y
y
y=L
y=ƒ
y=ƒ 0
y=L y=ƒ
y=L x
0
0
x
x
FIGURE 2 Examples illustrating lim f sxd − L xl`
Referring back to Figure 1, we see that for numerically large negative values of x, the values of f sxd are close to 1. By letting x decrease through negative values without bound, we can make f sxd as close to 1 as we like. This is expressed by writing lim
x l2`
x2 2 1 −1 x2 1 1
The general definition is as follows.
y
2 Definitio Let f be a function defined on some interval s2`, ad. Then y=ƒ
lim f sxd − L
x l 2`
means that the values of f sxd can be made arbitrarily close to L by requiring x to be sufficiently large negative.
y=L 0
x y
“the limit of f sxd, as x approaches negative infinity, is L” Definition 2 is illustrated in Figure 3. Notice that the graph approaches the line y − L as we look to the far left of each graph.
y=ƒ
y=L
Again, the symbol 2` does not represent a number, but the expression lim f sxd − L x l 2` is often read as
0
x
FIGURE 3 Examples illustrating lim f sxd − L
3 Definitio The line y − L is called a horizontal asymptote of the curve y − f sxd if either lim f sxd − L or lim f sxd − L x l`
x l 2`
x l 2`
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.6 Limits at Infini y; Horizontal Asymptotes y
129
For instance, the curve illustrated in Figure 1 has the line y − 1 as a horizontal asymp tote because x2 2 1 lim 2 −1 xl` x 1 1
π 2
0
x
An example of a curve with two horizontal asymptotes is y − tan21x. (See Figure 4.) In fact,
_ π2
4
lim tan21 x − 2 lim tan21 x − xl` 2 2
x l2`
FIGURE 4 y − tan21x
so both of the lines y − 2y2 and y − y2 are horizontal asymptotes. (This follows from the fact that the lines x − 6y2 are vertical asymptotes of the graph of the tangent function.) y
EXAMPLE 1 Find the infinite limits, limits at infinity, and asymptotes for the function f whose graph is shown in Figure 5. SOLUTION We see that the values of f sxd become large as x l 21 from both sides, so
2
lim f sxd − `
x l21
0
x
2
Notice that f sxd becomes large negative as x approaches 2 from the left, but large positive as x approaches 2 from the right. So lim f sxd − 2` and lim1 f sxd − `
x l 22
x l2
Thus both of the lines x − 21 and x − 2 are vertical asymptotes. As x becomes large, it appears that f sxd approaches 4. But as x decreases through negative values, f sxd approaches 2. So
FIGURE 5
lim f sxd − 4 and lim f sxd − 2
xl`
x l2`
This means that both y − 4 and y − 2 are horizontal asymptotes.
EXAMPLE 2 Find lim
xl`
n
1 1 and lim . x l2` x x
SOLUTION Observe that when x is large, 1yx is small. For instance, y
1 1 1 − 0.01 − 0.0001 − 0.000001 100 10,000 1,000,000
y=∆
0
FIGURE 6 lim
xl`
1 1 − 0, lim −0 x l2` x x
In fact, by taking x large enough, we can make 1yx as close to 0 as we please. Therefore, according to Definition 1, we have x
lim
xl`
1 −0 x
Similar reasoning shows that when x is large negative, 1yx is small negative, so we also have 1 lim −0 x l2` x It follows that the line y − 0 (the xaxis) is a horizontal asymptote of the curve y − 1yx. (This is a hyperbola; see Figure 6.)
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n
130
CHAPTER 2 Limits and Derivatives
■ Evaluating Limits at Infinity Most of the Limit Laws that were given in Section 2.3 also hold for limits at infinity. It can be proved that the Limit Laws listed in Section 2.3 (with the exception of Laws 10 and 11) are also valid if “x l a” is replaced by “x l `” or “x l 2`.” In particular, if we combine Laws 6 and 7 with the results of Example 2, we obtain the following important rule for calculating limits. 5 Theorem If r . 0 is a rational number, then lim
xl`
1 −0 xr
If r . 0 is a rational number such that x r is defined for all x, then lim
x l2`
1 −0 xr
EXAMPLE 3 Evaluate the following limit and indicate which properties of limits are used at each stage. 3x 2 2 x 2 2 lim x l ` 5x 2 1 4x 1 1 SOLUTION As x becomes large, both numerator and denominator become large, so it isn’t obvious what happens to their ratio. We need to do some preliminary algebra. To evaluate the limit at infinity of any rational function, we first divide both the numerator and denominator by the highest power of x that occurs in the denominator. (We may assume that x ± 0, since we are interested only in large values of x.) In this case the highest power of x in the denominator is x 2, so we have 3x 2 2 x 2 2 1 2 32 2 2 2 2 3x 2 x 2 2 x x x lim − lim − lim x l ` 5x 2 1 4x 1 1 x l ` 5x 2 1 4x 1 1 x l` 4 1 51 1 2 2 x x x
S S
1 2 2 2 x x − 4 1 lim 5 1 1 2 xl` x x lim 3 2
xl`
y
0
FIGURE 7 2
y−
3x 2 x 2 2 5x 2 1 4x 1 1
y=0.6
1
x
D D
1 2 2 lim x l` x l` x x l` − 1 lim 5 1 4 lim 1 lim x l` x l` x x l` lim 3 2 lim
−
32020 51010
−
3 5
(by Limit Law 5)
1 x2 (by 1, 2, and 3) 1 x2 (by 8 and Theorem 5)
A similar calculation shows that the limit as x l 2` is also 35. Figure 7 illustrates the
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SECTION 2.6 Limits at Infini y; Horizontal Asymptotes
131
results of these calculations by showing how the graph of the given rational function n approaches the horizontal asymptote y − 35 − 0.6.
EXAMPLE 4 Find the horizontal asymptotes of the graph of the function f sxd −
s2x 2 1 1 3x 2 5
SOLUTION Dividing both numerator and denominator by x (which is the highest power of x in the denominator) and using the properties of limits, we have s2x 2 1 1 x s2x 1 1 lim − lim − lim x l ` 3x 2 5 xl` xl` 3x 2 5 x 2
lim
−
xl`
lim
y
xl`
Î Î S D 32
2x 2 1 1 x2 (since sx 2 − x for x . 0) 3x 2 5 x
1 x 2 − s2 1 0 − s2 − 325?0 3 1 lim 3 2 5 lim xl` xl` x lim 2 1 lim
xl`
5 x
xl`
Therefore the line y − s2 y3 is a horizontal asymptote of the graph of f. In computing the limit as x l 2`, we must remember that for x , 0, we have sx 2 − x − 2x. So when we divide the numerator by x, for x , 0 we get
œ„2
 
y= 3
Î
s2x 2 1 1 s2x 2 1 1 − −2 x 2 sx 2
x œ„2
y=_ 3
Therefore s2x 1 1 − lim x l2` 3x 2 5 2
lim
x l2`
FIGURE 8 y−
1 x2
21
Î
s 2x 2 1 1 3x 2 5
Î
21
2
32
1 x2
5 x
Î
2x 2 1 1 −2 x2
1 x2
Î
2 −
21
1 x l2` x 2 s2 −2 1 3 3 2 5 lim x l2` x 2 1 lim
Thus the line y − 2s2 y3 is also a horizontal asymptote. See Figure 8.
n
EXAMPLE 5 Compute lim (sx 2 1 1 2 x). x l`
We can think of the given function as having a denominator of 1.
SOLUTION Because both sx 2 1 1 and x are large when x is large, it’s difficult to see what happens to their difference, so we use algebra to rewrite the function. We first multiply numerator and denominator by the conjugate radical: lim (sx 2 1 1 2 x) − lim (sx 2 1 1 2 x)
x l`
y
y=œ„„„„„x ≈+1 1 0
FIGURE 9
1
x
sx 2 1 1 1 x
sx 2 1 1 1 x sx 2 1 1d 2 x 2 1 − lim − lim x l ` sx 2 1 1 1 x x l ` sx 2 1 1 1 x x l`
Notice that the denominator of this last expression (sx 2 1 1 1 x) becomes large as x l ` (it’s bigger than x). So 1 lim (sx 2 1 1 2 x) − lim −0 x l` x l ` sx 2 1 1 1 x Figure 9 illustrates this result.
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n
132
CHAPTER 2 Limits and Derivatives
S D
1 . x22
EXAMPLE 6 Evaluate lim1 arctan x l2
SOLUTION If we let t − 1ysx 2 2d, we know that t l ` as x l 2 1. Therefore, by the second equation in (4), we have
S D
lim arctan
x l 21
1 x22
− lim arctan t − tl`
2
n
The graph of the natural exponential function y − e x has the line y − 0 (the xaxis) as a horizontal asymptote. (The same is true of any exponential function with base b . 1.) In fact, from the graph in Figure 10 and the corresponding table of values, we see that lim e x − 0
6
x l 2`
Notice that the values of e x approach 0 very rapidly. y
y=´
1 0
FIGURE 10
x
1
x
ex
0 21 22 23 25 28 210
1.00000 0.36788 0.13534 0.04979 0.00674 0.00034 0.00005
EXAMPLE 7 Evaluate lim2 e 1yx. x l0
PS The problemsolving strategy for
Examples 6 and 7 is introducing something extra (see Principles of Problem Solving following Chapter 1). Here, the something extra, the auxiliary aid, is the new variable t.
SOLUTION If we let t − 1yx, we know that t l 2` as x l 02. Therefore, by (6), lim e 1yx − lim e t − 0
x l 02
t l 2`
(See Exercise 81.)
n
EXAMPLE 8 Evaluate lim sin x. xl`
SOLUTION As x increases, the values of sin x oscillate between 1 and 21 infinitely often and so they don’t approach any definite number. Thus lim x l` sin x does not exist. n
■ Infinite Limits at Infinity The notation lim f sxd − `
x l`
is used to indicate that the values of f sxd become large as x becomes large. Similar meanings are attached to the following symbols: lim f sxd − ` lim f sxd − 2` lim f sxd − 2`
x l 2`
x l`
x l 2`
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SECTION 2.6 Limits at Infini y; Horizontal Asymptotes
133
EXAMPLE 9 Find lim x 3 and lim x 3. xl`
x l2`
SOLUTION When x becomes large, x 3 also becomes large. For instance, 10 3 − 1000 100 3 − 1,000,000 1000 3 − 1,000,000,000 y
In fact, we can make x 3 as big as we like by requiring x to be large enough. Therefore we can write
y=˛
0
lim x 3 − `
xl`
x
Similarly, when x is large negative, so is x 3. Thus lim x 3 − 2`
x l2`
FIGURE 11 lim x 3 − `, lim x 3 − 2`
xl`
These limit statements can also be seen from the graph of y − x 3 in Figure 11.
x l2`
n
Looking at Figure 10 we see that
y
y=´
lim e x − `
x l`
but, as Figure 12 demonstrates, y − e x becomes large as x l ` at a much faster rate than y − x 3. y=˛
100 0
EXAMPLE 10 Find lim sx 2 2 xd. x l`
x
1
SOLUTION Limit Law 2 says that the limit of a difference is the difference of the limits, provided that these limits exist. We cannot use Law 2 here because
FIGURE 12 x
lim x 2 − ` and lim x − `
x l`
3
e is much larger than x when x is large.
x l`
In general, the Limit Laws can’t be applied to infinite limits because ` is not a number (` 2 ` can’t be defined). However, we can write lim sx 2 2 xd − lim xsx 2 1d − `
x l`
x l`
because both x and x 2 1 become arbitrarily large and so their product does too.n
EXAMPLE 11 Find lim
xl`
x2 1 x . 32x
SOLUTION As in Example 3, we divide the numerator and denominator by the highest power of x in the denominator, which is simply x: lim
x l`
x2 1 x x11 − lim − 2` x l` 32x 3 21 x
because x 1 1 l ` and 3yx 2 1 l 0 2 1 − 21 as x l `.n
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134
CHAPTER 2 Limits and Derivatives
The next example shows that by using infinite limits at infinity, together with intercepts, we can get a rough idea of the graph of a polynomial without having to plot a large number of points.
EXAMPLE 12 Sketch the graph of y − sx 2 2d4sx 1 1d3sx 2 1d by finding its
intercepts and its limits as x l ` and as x l 2`.
SOLUTION The yintercept is f s0d − s22d4s1d3s21d − 216 and the xintercepts are found by setting y − 0: x − 2, 21, 1. Notice that since sx 2 2d4 is never negative, the function doesn’t change sign at 2; thus the graph doesn’t cross the xaxis at 2. The graph crosses the axis at 21 and 1. When x is large positive, all three factors are large, so
y
0
_1
1
2
x
lim sx 2 2d4sx 1 1d3sx 2 1d − `
xl`
When x is large negative, the first factor is large positive and the second and third factors are both large negative, so
_16
lim sx 2 2d4sx 1 1d3sx 2 1d − `
x l2`
FIGURE 13
y − sx 2 2d4 sx 1 1d3 sx 2 1d
Combining this information, we give a rough sketch of the graph in Figure 13.n
■ Precise Definitions Definition 1 can be stated precisely as follows. 7 Precise Definition of a Limit t Infini y Let f be a function defined on some interval sa, `d. Then lim f sxd − L
xl`
means that for every « . 0 there is a corresponding number N such that


if x . N then f sxd 2 L , « In words, this says that the values of f sxd can be made arbitrarily close to L (within a distance «, where « is any positive number) by requiring x to be sufficiently large (larger than N, where N depends on «). Graphically, it says that by keeping x large enough (larger than some number N) we can make the graph of f lie between the given horizontal lines y − L 2 « and y − L 1 « as in Figure 14. This must be true no matter how small we choose «. y
y=L+∑ ∑ L ∑ y=L∑
FIGURE 14
lim f sxd − L
xl`
0
y=ƒ ƒ is in here x
N when x is in here
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135
SECTION 2.6 Limits at Infini y; Horizontal Asymptotes
Figure 15 shows that if a smaller value of « is chosen, then a larger value of N may be required. y
L
y=ƒ
y=L+∑ y=L∑
0
FIGURE 15
N
x
lim f sxd − L
xl`
Similarly, a precise version of Definition 2 is given by Definition 8, which is illustrated in Figure 16.
8 Definitio Let f be a function defined on some interval s2`, ad. Then lim f sxd − L
x l 2`
means that for every « . 0 there is a corresponding number N such that


if x , N then f sxd 2 L , «
y
y=ƒ
y=L+∑ L y=L∑
FIGURE 16 lim f sxd − L
x
0
N
x l2`
In Example 3 we calculated that lim
xl`
3x 2 2 x 2 2 3 − 2 5x 1 4x 1 1 5
In the next example we use a calculator (or computer) to relate this statement to Definition 7 with L − 35 − 0.6 and « − 0.1.
EXAMPLE 13 Use a graph to find a number N such that if x . N then
Z
3x 2 2 x 2 2 2 0.6 5x 2 1 4x 1 1
Z
, 0.1
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136
CHAPTER 2 Limits and Derivatives
SOLUTION We rewrite the given inequality as 3x 2 2 x 2 2 , 0.7 5x 2 1 4x 1 1
0.5 , 1
We need to determine the values of x for which the given curve lies between the horizontal lines y − 0.5 and y − 0.7. So we graph the curve and these lines in Figure 17. Then we use the graph to estimate that the curve crosses the line y − 0.5 when x < 6.7. To the right of this number it seems that the curve stays between the lines y − 0.5 and y − 0.7. Rounding up to be safe, we can say that
y=0.7 y=0.5 y=
3≈x2 5≈+4x+1
15
0
FIGURE 17
if x . 7 then
Z
3x 2 2 x 2 2 2 0.6 5x 2 1 4x 1 1
Z
, 0.1
In other words, for « − 0.1 we can choose N − 7 (or any larger number) in Definition 7. 1 − 0. x
EXAMPLE 14 Use Definition 7 to prove that lim
xl`
SOLUTION Given « . 0, we want to find N such that if x . N then
n
Z
1 20 x
Z
,«
In computing the limit we may assume that x . 0. Then 1yx , « &? x . 1y«. Let’s choose N − 1y«. So if x . N −
Z
1 1 then 20 « x
Z
−
1 ,« x
Therefore, by Definition 7, lim
xl`
1 −0 x
Figure 18 illustrates the proof by showing some values of « and the corresponding values of N. y
y
∑=1 0
FIGURE 18
N=1
x
∑=0.2
0
y
N=5
x
∑=0.1
0
N=10
x
n
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137
SECTION 2.6 Limits at Infini y; Horizontal Asymptotes y M
Finally we note that an infinite limit at infinity can be defined as follows. The geometric illustration is given in Figure 19.
y=M
9 Precise Definition of an nfini e Limit at Infini y Let f be a function defined on some interval sa, `d. Then 0
x
N
lim f sxd − `
xl`
FIGURE 19
means that for every positive number M there is a corresponding positive number N such that
lim f sxd − `
xl`
if x . N then f sxd . M
Similar definitions apply when the symbol ` is replaced by 2`. (See Exercise 80.)
2.6 Exercises y
1. Explain in your own words the meaning of each of the following. (a) lim f sxd − 5 (b) lim f sxd − 3 xl`
x l 2`
1
2. (a) Can the graph of y − f sxd intersect a vertical asymptote? Can it intersect a horizontal asymptote? Illustrate by sketching graphs. (b) How many horizontal asymptotes can the graph of y − f sxd have? Sketch graphs to illustrate the possibilities. 3. For the function f whose graph is given, state the following. (a) lim f sxd (b) lim f sxd x l`
x l 2`
(c) lim f sxd (d) lim f sxd x l1
x l3
x
1
5–10 Sketch the graph of an example of a function f that satisfies all of the given conditions. 5. f s2d − 4, f s22d − 24, lim f sxd − 0, lim f sxd − 2 x l 2`
(e) The equations of the asymptotes
x l`
6. f s0d − 0, lim2 f sxd − `, lim1 f sxd − 2`, x l1
y
x l1
lim f sxd − 22, lim f sxd − 22 x l 2`
x l`
7. lim f sxd − `, lim2 f sxd − 2`, lim1 f sxd − `,
1
x l0
1
x
x l3
x l3
lim f sxd − 1, lim f sxd − 21 x l 2`
x l`
8. lim f sxd − 2`, lim 2 f sxd − `, lim 1 f sxd − 2`, x l 2`
x l 22
x l 22
lim f sxd − `, lim f sxd − ` x l2
x l`
9. f s0d − 0, lim f sxd − 2`, lim f sxd − 2`, f is odd
4. For the function t whose graph is given, state the following. (a) lim tsxd (b) lim tsxd
10. lim f sxd − 21, lim2 f sxd − `, lim1 f sxd − 2`,
(c) lim tsxd (d) lim2 tsxd
lim2 f sxd − 1, f s3d − 4, lim1 f sxd − 4, lim f sxd − 1
x l` xl0
(e) lim1 tsxd x l2
x l 2` xl2
x l1
x l 2` x l3
x l`
x l0
x l0
x l3
x l`
(f) The equations of the asymptotes
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138
CHAPTER 2 Limits and Derivatives
; 11. Guess the value of the limit lim
x l`
37. lim
xl`
x2 2x
39.
by evaluating the function f sxd − x 2y2 x for x − 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, and 100. Then use a graph of f to support your guess.
lim
x lsy2d1
S D
f sxd − 1 2
2 x
2
2x 2 7 5x 2 1 x 2 3
14. lim
xl`
Î
3
9x 1 8x 2 4 3 2 5x 1 x 3
15–42 Find the limit or show that it does not exist. 4x 1 3 15. lim x l ` 5x 2 1
22 16. lim x l ` 3x 1 7
41. lim flns1 1 x d 2 lns1 1 xdg xl `
42. lim flns2 1 xd 2 lns1 1 xdg
3t 1 t t 3 2 4t 1 1
r 2 r3 19. lim r l ` 2 2 r 2 1 3r 3 21. lim
xl`
4 2 sx
2 1 sx
sx 1 3x 2 23. lim xl` 4x 2 1
6t 1 t 2 5 9 2 2t 2
18. lim
t l 2`
3x 3 2 8x 1 2 20. lim x l ` 4x 3 2 5x 2 2 2 22. lim
u l 2`
24. lim
tl`
su 2 1 1ds2u 2 2 1d su 2 1 2d2 t13
s2t 2 2 1
25. lim
s1 1 4x 6 2 2 x3
26. lim
s1 1 4x 6 2 2 x3
27. lim
2x 5 2 x x4 1 3
28. lim
q 3 1 6q 2 4 4q 2 2 3q 1 3
xl`
x l 2`
29. lim (s25t 2 1 2 2 5t) tl`
x l 2`
ql`
30. lim (s4x 2 1 3x 1 2 x ) x l2`
31. lim (sx 2 1 ax 2 sx 2 1 bx x l`
32. lim ( x 2 sx xl`
)
34. lim se2x 1 2 cos 3xd
35. lim se22x cos xd
sin2 x 36. lim 2 xl` x 1 1
x l 2`
xl`
xl0
(ii) lim2 f sxd
(iii) lim1 f sxd
xl1
x l1
(b) Use a table of values to estimate lim f sxd. xl`
(c) Use the information from parts (a) and (b) to make a rough sketch of the graph of f. 44. (a) For f sxd −
2 1 2 find each of the following limits. x ln x
(i) lim f sxd xl`
(ii) lim1 f sxd
(iii) lim2 f sxd
(iv) lim1 f sxd
xl1
xl0 x l1
(b) Use the information from part (a) to make a rough sketch of the graph of f. ; 45. (a) Estimate the value of lim (sx 2 1 x 1 1 1 x)
x l 2`
by graphing the function f sxd − sx 2 1 x 1 1 1 x. (b) Use a table of values of f sxd to guess the value of the limit. (c) Prove that your guess is correct. ; 46. (a) Use a graph of f sxd − s3x 2 1 8x 1 6 2 s3x 2 1 3x 1 1 to estimate the value of lim x l ` f sxd to one decimal place. (b) Use a table of values of f sxd to estimate the limit to four decimal places. (c) Find the exact value of the limit. 47–52 Find the horizontal and vertical asymptotes of each curve. You may want to use a graphing calculator (or computer) to check your work by graphing the curve and estimating the asymptotes. 47. y −
5 1 4x x13
48. y −
2x 2 1 1 3x 1 2x 2 1
49. y −
2x 2 1 x 2 1 x2 1 x 2 2
50. y −
1 1 x4 x2 2 x4
51. y −
x3 2 x x 2 6x 1 5
52. y −
2e x e 25
)
33. lim sx 2 1 2x 7 d
x find each of the following limits. ln x
(i) lim1 f sxd
2
2
t l 2`
xl0
43. (a) For f sxd −
13–14 Evaluate the limit and justify each step by indicating the appropriate properties of limits.
17. lim
e 3x 2 e23x e 3x 1 e23x
40. lim1 tan21sln xd
e sec x
x
to estimate the value of lim x l ` f sxd correct to two decimal places. (b) Use a table of values of f sxd to estimate the limit to four decimal places.
xl`
xl`
2
13. lim
38. lim
xl `
; 12. (a) Use a graph of
1 2 ex 1 1 2e x
xl`
2
2
x
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SECTION 2.6 Limits at Infini y; Horizontal Asymptotes
; 53. Estimate the horizontal asymptote of the function f sxd −
3x 3 1 500x 2 x 1 500x 2 1 100x 1 2000 3
b y graphing f for 210 < x < 10. Then calculate the equation of the asymptote by evaluating the limit. How do you explain the discrepancy?
139
60–64 Find the limits as x l ` and as x l 2`. Use this information, together with intercepts, to give a rough sketch of the graph as in Example 12. 60. y − 2x 3 2 x 4
61. y − x 4 2 x 6
62. y − x 3sx 1 2d 2sx 2 1d 63. y − s3 2 xds1 1 xd 2s1 2 xd 4
; 54. (a) Graph the function
64. y − x 2sx 2 2 1d 2sx 1 2d
s2x 1 1 f sxd − 3x 2 5 2
How many horizontal and vertical asymptotes do you observe? Use the graph to estimate the values of the limits
lim
x l`
s2x 2 1 1 s2x 2 1 1 and lim x l 2` 3x 2 5 3x 2 5
(b) By calculating values of f sxd, give numerical estimates of the limits in part (a). (c) Calculate the exact values of the limits in part (a). Did you get the same value or different values for these two limits? [In view of your answer to part (a), you might have to check your calculation for the second limit.]
55. Let P and Q be polynomials. Find lim
xl`
Psxd Qsxd
sin x . x (b) Graph f sxd − ssin xdyx. How many times does the graph cross the asymptote?
65. (a) Use the Squeeze Theorem to evaluate lim
xl`
;
; 66. E nd Behavior of a Function By the end behavior of a function we mean the behavior of its values as x l ` and as x l 2`. (a) Describe and compare the end behavior of the functions Psxd − 3x 5 2 5x 3 1 2x Qsxd − 3x 5 by graphing both functions in the viewing rectangles f22, 2g by f22, 2g and f210, 10g by f210,000, 10,000g. (b) Two functions are said to have the same end behavior if their ratio approaches 1 as x l `. Show that P and Q have the same end behavior. 67. Find lim x l ` f sxd if, for all x . 1, 10e x 2 21 5sx , f sxd , 2e x sx 2 1
if the degree of P is (a) less than the degree of Q and (b) greater than the degree of Q. 56. M ake a rough sketch of the curve y − x n (n an integer) for the following five cases: (i) n − 0 (ii) n . 0, n odd (iii) n . 0, n even (iv) n , 0, n odd (v) n , 0, n even Then use these sketches to find the following limits. (a) lim1 x n (b) lim2 x n
68. (a) A tank contains 5000 L of pure water. Brine that contains 30 g of salt per liter of water is pumped into the tank at a rate of 25 Lymin. Show that the concentration of salt after t minutes (in grams per liter) is
(c) lim x n (d) lim x n
x l0
x l0
x l`
Cstd −
69. I n Chapter 9 we will be able to show, under certain assump tions, that the velocity vstd of a falling raindrop at time t is vstd − v *s1 2 e 2ttyv * d
lim f sxd − 0, lim f sxd − 2`, f s2d − 0, x l0
lim2 f sxd − `, lim1 f sxd − 2`
x l3
(b) What happens to the concentration as t l ` ?
x l 2`
57. F ind a formula for a function f that satisfies the following conditions: x l 6`
30t 200 1 t
x l3
58. F ind a formula for a function that has vertical asymptotes x − 1 and x − 3 and horizontal asymptote y − 1. 59. A function f is a ratio of quadratic functions and has a vertical asymptote x − 4 and just one xintercept, x − 1. It is known that f has a removable discontinuity at x − 21 and lim x l21 f sxd − 2. Evaluate (a) f s0d (b) lim f sxd xl`
;
where t is the acceleration due to gravity and v * is the terminal velocity of the raindrop. (a) Find lim t l ` vstd. (b) Graph vstd if v* − 1 mys and t − 9.8 mys2. How long does it take for the velocity of the raindrop to reach 99% of its terminal velocity?
2xy10 and y − 0.1 on a common ; 70. (a) By graphing y − e screen, discover how large you need to make x so that e 2xy10 , 0.1. (b) Can you solve part (a) without using a graph?
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
140
CHAPTER 2 Limits and Derivatives
; 71. Use a graph to find a number N such that
Z
Z
3x2 1 1 2 1.5 , 0.05 2x 2 1 x 1 1
if x . N then
76. (a) How large do we have to take x so that 1ysx , 0.0001?
(b) Taking r − 12 in Theorem 5, we have the statement lim
xl`
; 72. For the limit lim
xl`
1 2 3x sx 1 1 2
− 23
illustrate Definition 7 by finding values of N that correspond to « − 0.1 and « − 0.05. ; 73. For the limit 1 2 3x
lim
x l2`
sx 1 1 2
−0
77. Use Definition 8 to prove that lim
x l2`
1 − 0. x
78. Prove, using Definition 9, that lim x 3 − `. xl`
79. Use Definition 9 to prove that lim e x − `. xl`
−3
80. Formulate a precise definition of lim f sxd − 2`
x l2`
Then use your definition to prove that
; 74. For the limit
lim s1 1 x 3 d − 2`
lim sx ln x − `
x l2`
xl`
illustrate Definition 9 by finding a value of N that corresponds to M − 100. 75. (a) How large do we have to take x so that 1yx 2 , 0.0001? (b) Taking r − 2 in Theorem 5, we have the statement 1 lim −0 xl` x2
sx
Prove this directly using Definition 7.
illustrate Definition 8 by finding values of N that correspond to « − 0.1 and « − 0.05.
1
81. (a) Prove that lim f sxd − lim1 f s1ytd tl0
xl`
and
f s1ytd lim f sxd − t lim l 02
xl2`
assuming that these limits exist. (b) Use part (a) and Exercise 65 to find lim x sin
Prove this directly using Definition 7.
x l 01
1 x
2.7 Derivatives and Rates of Change Now that we have defined limits and have learned techniques for computing them, we revisit the problems of finding tangent lines and velocities from Section 2.1. The special type of limit that occurs in both of these problems is called a derivative and we will see that it can be interpreted as a rate of change in any of the natural or social sciences or engineering.
■ Tangents If a curve C has equation y − f sxd and we want to find the tangent line to C at the point Psa, f sadd, then we consider (as we did in Section 2.1) a nearby point Qsx, f sxdd, where x ± a, and compute the slope of the secant line PQ: mPQ −
f sxd 2 f sad x2a
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SECTION 2.7 Derivatives and Rates of Change y
Then we let Q approach P along the curve C by letting x approach a. If mPQ approaches a number m, then we define the tangent line , to be the line through P with slope m. (This amounts to saying that the tangent line is the limiting position of the secant line PQ ƒf(a) as Q approaches P. See Figure 1.)
Q{ x, ƒ } P { a, f(a)} xa
1 Definitio The tangent line to the curve y − f sxd at the point Psa, f sadd is the line through P with slope
a
0
y
141
x
x
m − lim
xla
f sxd 2 f sad x2a
provided that this limit exists.
L Q
In our first example we confirm the guess we made in Example 2.1.1.
Q Q
P
EXAMPLE 1 Find an equation of the tangent line to the parabola y − x 2 at the point Ps1, 1d. SOLUTION Here we have a − 1 and f sxd − x 2, so the slope is x
0
m − lim
x l1
FIGURE 1
− lim
x l1
f sxd 2 f s1d x2 2 1 − lim x l1 x 2 1 x21 sx 2 1dsx 1 1d x21
− lim sx 1 1d − 1 1 1 − 2 x l1
Using the pointslope form of the equation of a line, we find that an equation of the tangent line at s1, 1d is
Pointslope form for a line through the point sx1 , y1 d with slope m: y 2 y1 − msx 2 x 1 d
y 2 1 − 2sx 2 1d or y − 2x 2 1
n
We sometimes refer to the slope of the tangent line to a curve at a point as the slope of the curve at the point. The idea is that if we zoom in far enough toward the point, the curve looks almost like a straight line. Figure 2 illustrates this procedure for the curve y − x 2 in Example 1. The more we zoom in, the more the parabola looks like a line. In other words, the curve becomes almost indistinguishable from its tangent line. 2
1.5
(1, 1)
0
1.1
(1, 1)
2
0.5
(1, 1)
1.5
0.9
FIGURE 2 Zooming in toward the point (1, 1) on the parabola y − x 2
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1.1
142
CHAPTER 2 Limits and Derivatives
y
L
Q { a+h, f(a+h)}
There is another expression for the slope of a tangent line that is sometimes easier to use. If h − x 2 a, then x − a 1 h and so the slope of the secant line PQ is
P { a, f(a)}
mPQ − f(a+h)f(a)
h 0
a
a+h
x
FIGURE 3
f sa 1 hd 2 f sad h
(See Figure 3 where the case h . 0 is illustrated and Q is located to the right of P. If it happened that h , 0, however, Q would be to the left of P.) Notice that as x approaches a, h approaches 0 (because h − x 2 a) and so the expression for the slope of the tangent line in Definition 1 becomes
2
m − lim
hl0
f sa 1 hd 2 f sad h
EXAMPLE 2 Find an equation of the tangent line to the hyperbola y − 3yx at the
point s3, 1d.
SOLUTION Let f sxd − 3yx. Then, by Equation 2, the slope of the tangent at s3, 1d is m − lim
hl0
f s3 1 hd 2 f s3d h
3 3 2 s3 1 hd 21 31h 31h − lim − lim hl0 hl0 h h y
− lim
3 y= x
x+3y6=0
hl0
Therefore an equation of the tangent at the point s3, 1d is
(3, 1)
y 2 1 − 213 sx 2 3d
x
0
which simplifies to FIGURE 4 position at time t=a+h
f(a+h)f(a)
f(a) f(a+h)
FIGURE 5
x 1 3y 2 6 − 0
The hyperbola and its tangent are shown in Figure 4.
position at time t=a 0
2h 1 1 − lim 2 −2 hl0 hs3 1 hd 31h 3
s
n
■ Velocities In Section 2.1 we investigated the motion of a ball dropped from the CN Tower and defined its velocity to be the limiting value of average velocities over shorter and shorter time periods. In general, suppose an object moves along a straight line according to an equation of motion s − f std, where s is the displacement (directed distance) of the object from the origin at time t. The function f that describes the motion is called the position function of the object. In the time interval from t − a to t − a 1 h , the change in position is f sa 1 hd 2 f sad. (See Figure 5.)
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 2.7 Derivatives and Rates of Change s
Q { a+h, f(a+h)}
The average velocity over this time interval is average velocity −
P { a, f(a)} h
0
a
mPQ=
a+h
t
f(a+h)f(a) h
143
displacement f sa 1 hd 2 f sad − time h
which is the same as the slope of the secant line PQ in Figure 6. Now suppose we compute the average velocities over shorter and shorter time intervals fa, a 1 hg. In other words, we let h approach 0. As in the example of the falling ball, we define the velocity (or instantaneous velocity) vsad at time t − a to be the limit of these average velocities.
average velocity
FIGURE 6
3 Definitio The instantaneous velocity of an object with position function f std at time t − a is vsad − lim
hl0
f sa 1 hd 2 f sad h
provided that this limit exists. This means that the velocity at time t − a is equal to the slope of the tangent line at P (compare Equation 2 and the expression in Definition 3). Now that we know how to compute limits, let’s reconsider the problem of the falling ball from Example 2.1.3.
EXAMPLE 3 Suppose that a ball is dropped from the upper observation deck of the CN Tower, 450 m above the ground. (a) What is the velocity of the ball after 5 seconds? (b) How fast is the ball traveling when it hits the ground? Recall from Section 2.1: The distance (in meters) fallen after t seconds is 4.9t 2.
SOLUTION Since two different velocities are requested, it’s efficient to start by finding the velocity at a general time t − a. Using the equation of motion s − f std − 4.9t 2, we have v sad − lim
hl0
f sa 1 hd 2 f sad 4.9sa 1 hd2 2 4.9a 2 − lim hl0 h h
− lim
4.9sa 2 1 2ah 1 h 2 2 a 2 d 4.9s2ah 1 h 2 d − lim hl0 h h
− lim
4.9hs2a 1 hd − lim 4.9s2a 1 hd − 9.8a hl0 h
hl0
hl0
(a) The velocity after 5 seconds is vs5d − s9.8ds5d − 49 mys. (b) Since the observation deck is 450 m above the ground, the ball will hit the ground at the time t when sstd − 450, that is, 4.9t 2 − 450 This gives t2 −
450 and t − 4.9
Î
450 < 9.6 s 4.9
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
144
CHAPTER 2 Limits and Derivatives
The velocity of the ball as it hits the ground is therefore
v
SÎ D Î 450 4.9
− 9.8
450 < 94 mys 4.9
n
■ Derivatives We have seen that the same type of limit arises in finding the slope of a tangent line (Equation 2) or the velocity of an object (Definition 3). In fact, limits of the form lim
h l0
f sa 1 hd 2 f sad h
arise whenever we calculate a rate of change in any of the sciences or engineering, such as a rate of reaction in chemistry or a marginal cost in economics. Since this type of limit occurs so widely, it is given a special name and notation. 4 Definitio The derivative of a function f at a number a, denoted by f 9sad, is f 9sad − lim
f 9sad is read “ f prime of a.”
h l0
f sa 1 hd 2 f sad h
if this limit exists. If we write x − a 1 h, then we have h − x 2 a and h approaches 0 if and only if x approaches a. Therefore an equivalent way of stating the definition of the derivative, as we saw in finding tangent lines (see Definition 1), is
5
f 9sad − lim
xla
f sxd 2 f sad x2a
EXAMPLE 4 Use Definition 4 to find the derivative of the function f sxd − x 2 2 8x 1 9 at the numbers (a) 2 and (b) a. Definitions 4 and 5 are equivalent, so we can use either one to compute the derivative. In practice, Definition 4 often leads to simpler computations.
SOLUTION (a) From Definition 4 we have f 9s2d − lim
h l0
f s2 1 hd 2 f s2d h
− lim
s2 1 hd2 2 8s2 1 hd 1 9 2 s23d h
− lim
4 1 4h 1 h 2 2 16 2 8h 1 9 1 3 h
− lim
h 2 2 4h hsh 2 4d − lim − lim sh 2 4d − 24 h l0 h l0 h h
h l0
h l0
h l0
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SECTION 2.7 Derivatives and Rates of Change
(b)
145
f sa 1 hd 2 f sad h
f 9sad − lim
h l0
− lim
fsa 1 hd2 2 8sa 1 hd 1 9g 2 fa 2 2 8a 1 9g h
− lim
a 2 1 2ah 1 h 2 2 8a 2 8h 1 9 2 a 2 1 8a 2 9 h
− lim
2ah 1 h 2 2 8h − lim s2a 1 h 2 8d − 2a 2 8 h l0 h
h l0
h l0
h l0
As a check on our work in part (a), notice that if we let a − 2, then f 9s2d − 2s2d 2 8 − 24.
n
EXAMPLE 5 Use Equation 5 to find the derivative of the function f sxd − 1ysx at the number a sa . 0d. SOLUTION From Equation 5 we get f sxd 2 f sad x2a
f 9sad − lim
xla
1
1
1
2
1
sx sa sx sa sx sa − lim ? xla x2a x2a sx sa
− lim
xla
sa 2 sx
− lim
sax sx 2 ad
xla
− lim
xla
sa 2 sx sax sx 2 ad
2sx 2 ad
− lim
sax sx 2 ad(sa 1 sx )
xla
−
2
21 sa (sa 1 sa ) 2
−
21 a ? 2 sa
− lim
xla
−2
?
sa 1 sx sa 1 sx 21
sax (sa 1 sx )
1 2a3y2
You can verify that using Definition 4 gives the same result.
n
We defined the tangent line to the curve y − f sxd at the point Psa, f sadd to be the line that passes through P and has slope m given by Equation 1 or 2. Since, by Definition 4 (and Equation 5), this is the same as the derivative f 9sad, we can now say the following.
The tangent line to y − f sxd at sa, f sadd is the line through sa, f sadd whose slope is equal to f 9sad, the derivative of f at a.
If we use the pointslope form of the equation of a line, we can write an equation of the tangent line to the curve y − f sxd at the point sa, f sadd: y 2 f sad − f 9sadsx 2 ad
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
146
CHAPTER 2 Limits and Derivatives
y
EXAMPLE 6 Find an equation of the tangent line to the parabola y − x 2 2 8x 1 9 at
the point s3, 26d.
y=≈8x+9
0
x
SOLUTION From Example 4(b) we know that the derivative of f sxd − x 2 2 8x 1 9 at the number a is f 9sad − 2a 2 8. Therefore the slope of the tangent line at s3, 26d is f 9s3d − 2s3d 2 8 − 22. Thus an equation of the tangent line, shown in Figure 7, is y 2 s26d − s22dsx 2 3d or y − 22x
(3, _6)
n
■ Rates of Change
y=_2x
Suppose y is a quantity that depends on another quantity x. Thus y is a function of x and we write y − f sxd. If x changes from x 1 to x 2 , then the change in x (also called the increment of x) is Dx − x 2 2 x 1
FIGURE 7
and the corresponding change in y is Dy − f sx 2d 2 f sx 1d The difference quotient Dy f sx 2d 2 f sx 1d − Dx x2 2 x1 is called the average rate of change of y with respect to x over the interval fx 1, x 2g and can be interpreted as the slope of the secant line PQ in Figure 8. y
Q { ¤, ‡} P {⁄, fl}
Îy Îx
0
⁄
¤
x
average rate of change mPQ
instantaneous rate of change slope of tangent at P
FIGURE 8
By analogy with velocity, we consider the average rate of change over smaller and smaller intervals by letting x 2 approach x 1 and therefore letting Dx approach 0. The limit of these average rates of change is called the (instantaneous) rate of change of y with respect to x at x − x1, which (as in the case of velocity) is interpreted as the slope of the tangent to the curve y − f sxd at Psx 1, f sx 1dd: 6
instantaneous rate of change − lim
Dx l 0
Dy f sx2 d 2 f sx1d − lim x lx Dx x2 2 x1 2
1
We recognize this limit as being the derivative f 9sx 1d. We know that one interpretation of the derivative f 9sad is as the slope of the tangent line to the curve y − f sxd when x − a. We now have a second interpretation: The derivative f 9sad is the instantaneous rate of change of y − f sxd with respect to x when x − a.
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SECTION 2.7 Derivatives and Rates of Change y
Q
P
x
FIGURE 9 The yvalues are changing rapidly at P and slowly at Q.
147
The connection with the first interpretation is that if we sketch the curve y − f sxd, then the instantaneous rate of change is the slope of the tangent to this curve at the point where x − a. This means that when the derivative is large (and therefore the curve is steep, as at the point P in Figure 9), the yvalues change rapidly. When the derivative is small, the curve is relatively flat (as at point Q) and the yvalues change slowly. In particular, if s − f std is the position function of a particle that moves along a straight line, then f 9sad is the rate of change of the displacement s with respect to the time t. In other words, f 9sad is the velocity of the particle at time t − a. The speed of the particle is the absolute value of the velocity, that is, f 9sad . In the next example we discuss the meaning of the derivative of a function that is defined verbally.


EXAMPLE 7 A manufacturer produces bolts of a fabric with a fixed width. The cost of producing x meters of this fabric is C − f sxd dollars. (a) What is the meaning of the derivative f 9sxd? What are its units? (b) In practical terms, what does it mean to say that f 9s1000d − 9? (c) Which do you think is greater, f 9s50d or f 9s500d? What about f 9s5000d? SOLUTION (a) The derivative f 9sxd is the instantaneous rate of change of C with respect to x; that is, f 9sxd means the rate of change of the production cost with respect to the number of meters produced. (Economists call this rate of change the marginal cost. This idea is discussed in more detail in Sections 3.7 and 4.7.) Because DC f 9sxd − lim Dx l 0 Dx
Here we are assuming that the cost function is well behaved; in other words, Csxd doesn’t oscillate rapidly near x − 1000.
the units for f 9sxd are the same as the units for the difference quotient DCyDx. Since DC is measured in dollars and Dx in meters, it follows that the units for f 9sxd are dollars per meter. (b) The statement that f 9s1000d − 9 means that, after 1000 meters of fabric have been manufactured, the rate at which the production cost is increasing is $9ymeter. (When x − 1000, C is increasing 9 times as fast as x.) Since Dx − 1 is small compared with x − 1000, we could use the approximation f 9s1000d
4
(a) Find f 92s4d and f 91s4d. (b) Sketch the graph of f. (c) Where is f discontinuous? (d) Where is f not differentiable?
2
66. W hen you turn on a hotwater faucet, the temperature T of the water depends on how long the water has been running. In Example 1.1.4 we sketched a possible graph of T as a function of the time t that has elapsed since the faucet was turned on. (a) Describe how the rate of change of T with respect to t varies as t increases. (b) Sketch a graph of the derivative of T.
68. L et be the tangent line to the parabola y − x 2 at the point s1, 1d. The angle of inclination of is the angle that makes with the positive direction of the xaxis. Calculate correct to the nearest degree.
REVIEW
CONCEPT CHECK
Answers to the Concept Check are available at StewartCalculus.com.
1. Explain what each of the following means and illustrate with a sketch. (a) lim f sxd − L (b) lim1 f sxd − L (c) lim2 f sxd − L x la
x la
x la
(d) lim f sxd − ` (e) lim f sxd − L x la
x l`
2. Describe several ways in which a limit can fail to exist. Illustrate with sketches. 3. State the following Limit Laws. (a) Sum Law (b) Difference Law (c) Constant Multiple Law (d) Product Law (e) Quotient Law (f ) Power Law (g) Root Law 4. What does the Squeeze Theorem say? 5. (a) What does it mean to say that the line x − a is a vertical asymptote of the curve y − f sxd? Draw curves to illustrate the various possibilities. (b) What does it mean to say that the line y − L is a horizontal asymptote of the curve y − f sxd? Draw curves to illustrate the various possibilities.
6. Which of the following curves have vertical asymptotes? Which have horizontal asymptotes? (a) y − x 4 (b) y − sin x (c) y − tan x (d) y − tan21x (e) y − e x (f ) y − ln x (g) y − 1yx (h) y − sx 7. (a) What does it mean for f to be continuous at a? (b) What does it mean for f to be continuous on the interval s2`, `d? What can you say about the graph of such a function? 8. (a) Give examples of functions that are continuous on f21, 1g. (b) Give an example of a function that is not continuous on f0, 1g. 9. What does the Intermediate Value Theorem say? 10. W rite an expression for the slope of the tangent line to the curve y − f sxd at the point sa, f sadd. 11. S uppose an object moves along a straight line with position f std at time t. Write an expression for the instantaneous velocity of the object at time t − a. How can you interpret this velocity in terms of the graph of f ?
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
CHAPTER 2 Review
167
12. If y − f sxd and x changes from x 1 to x 2, write expressions for the following.
14. D efine the second derivative of f. If f std is the position function of a particle, how can you interpret the second derivative?
(a) The average rate of change of y with respect to x over the interval fx 1, x 2 g
(b) The instantaneous rate of change of y with respect to x at x − x 1
15. (a) What does it mean for f to be differentiable at a? (b) What is the relation between the differentiability and continuity of a function? (c) Sketch the graph of a function that is continuous but not differentiable at a − 2.
13. D efine the derivative f 9sad. Discuss two ways of interpreting this number.
16. D escribe several ways in which a function can fail to be differentiable. Illustrate with sketches.
TRUEFALSE QUIZ Determine whether the statement is true or false. If it is true, explain why. If it is false, explain why or give an example that disproves the statement. 1. lim
x l4
S
8 2x 2 x24 x24
D
− lim
x l4
2x 8 2 lim x l4 x 2 4 x24
lim sx 2 1 6x 2 7d x 2 1 6x 2 7 x l1 2. lim 2 − x l 1 x 1 5x 2 6 lim sx 2 1 5x 2 6d x l1
3. lim
xl1
lim sx 2 3d x23 xl1 − 2 lim sx 2 1 2x 2 4d x 1 2x 2 4 xl1
2
4.
x 29 −x13 x23 2
5. lim
xl3
x 29 − lim sx 1 3d xl3 x23
6. If lim x l 5 f sxd − 2 and lim x l 5 tsxd − 0, then limx l 5 f f sxdytsxdg does not exist.
12. A function can have two different horizontal asymptotes. 13. If f has domain f0, `d and has no horizontal asymptote, then lim x l ` f sxd − ` or lim x l ` f sxd − 2`. 14. I f the line x − 1 is a vertical asymptote of y − f sxd, then f is not defined at 1. 15. If f s1d . 0 and f s3d , 0, then there exists a number c between 1 and 3 such that f scd − 0. 16. If f is continuous at 5 and f s5d − 2 and f s4d − 3, then lim x l 2 f s4x 2 2 11d − 2. 17. If f is continuous on f21, 1g and f s21d − 4 and f s1d − 3, then there exists a number r such that r , 1 and f srd − .
 
18. Let f be a function such that lim x l 0 f sxd − 6. Then there exists a positive number such that if 0 , x , , then f sxd 2 6 , 1.

 

19. If f sxd . 1 for all x and lim x l 0 f sxd exists, then lim x l 0 f sxd . 1. 20. If f is continuous at a, then f is differentiable at a.
7. If lim x l5 f sxd − 0 and lim x l 5 tsxd − 0, then lim x l 5 f f sxdytsxdg does not exist.
21. If f 9srd exists, then lim x l r f sxd − f srd.
8. If neither lim x l a f sxd nor lim x l a tsxd exists, then lim x l a f f sxd 1 tsxdg does not exist.
d 2y 22. 2 − dx
9. If lim x l a f sxd exists but lim x l a tsxd does not exist, then lim x l a f f sxd 1 tsxdg does not exist.
23. The equation x 10 2 10x 2 1 5 − 0 has a solution in the interval s0, 2d.
10. If p is a polynomial, then lim x l b psxd − psbd. 11. If lim x l 0 f sxd − ` and lim x l 0 tsxd − `, then lim x l 0 f f sxd 2 tsxdg − 0.
S D dy dx
2
 
24. If f is continuous at a, so is f .
 
25. If f is continuous at a, so is f .
 
26. If f is differentiable at a, so is f .
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
168
CHAPTER 2 Limits and Derivatives
EXERCISES 1. The graph of f is given.
19. lim1 tan21s1yxd
20. lim
x l0
y
xl1
S
1 1 1 2 x21 x 2 3x 1 2
D
; 21–22 Use graphs to discover the asymptotes of the curve. Then prove what you have discovered. 21. y −
1 0
x
1
cos2 x x2
22. y − sx 2 1 x 1 1 2 sx 2 2 x
23. If 2x 2 1 < f sxd < x 2 for 0 , x , 3, find lim x l1 f sxd. 24. Prove that lim x l 0 x 2 coss1yx 2 d − 0.
(a) Find each limit, or explain why it does not exist. (i) lim1 f sxd (ii) lim 1 f sxd (iii) lim f sxd x l2
x l 23
x l 23
(iv) lim f sxd (v) lim f sxd (vi) lim2 f sxd x l4
x l0
27. lim sx 2 2 3xd − 22
28. lim1
29. Let
2. Sketch the graph of a function f that satisfies all of the following conditions: lim f sxd − 22, lim f sxd − 0, lim f sxd − `,
3 26. lim s x −0
xl2
xl`
x l 23
lim f sxd − 2`, lim1 f sxd − 2,
x l 32
x l3
xl0
x l3
x2 2 9 x 1 2x 2 3
2
5. lim
x l 23
x 29 x 2 1 2x 2 3
7. lim
sh 2 1d3 1 1 h
9. lim
sr sr 2 9d4
hl0
rl9
r 2 2 3r 2 4 11. lim r l 21 4r 2 1 r 2 3 13. lim
xl`
sx 2 2 9 2x 2 6
6. lim1 x l1
8. lim
t l2
x 29 x 2 1 2x 2 3
t2 2 4 t3 2 8
10. lim1 vl4

42v 42v

14. lim
x l 2`
sx 2 2 9 2x 2 6
16. lim
17. lim (sx 2 1 4x 1 1 2 x)
18. lim e x 2x
xl`
x l 2`
4
1 2 2x 2 x 5 1 x 2 3x 4
15. lim2 lnssin xd
2
(v) lim1 f sxd x l3
(iii) lim f sxd xl0
(vi) lim f sxd x l3
2x 2 x 2 22x x24
if if if if
0 2 Give a formula for t9 and sketch the graphs of t and t9.

77. (a) For what values of x is the function f sxd − x 2 2 9 differentiable? Find a formula for f 9. (b) Sketch the graphs of f and f 9.

 


78. W here is the function hsxd − x 2 1 1 x 1 2 differenti able? Give a formula for h9 and sketch the graphs of h and h9. 79. F ind the parabola with equation y − ax 2 1 bx whose tangent line at (1, 1) has equation y − 3x 2 2. 80. S uppose the curve y − x 4 1 ax 3 1 bx 2 1 cx 1 d has a tangent line when x − 0 with equation y − 2x 1 1 and a tangent line when x − 1 with equation y − 2 2 3x. Find the values of a, b, c, and d. 81. F or what values of a and b is the line 2x 1 y − b tangent to the parabola y − ax 2 when x − 2? 82. F ind the value of c such that the line y − 32 x 1 6 is tangent to the curve y − csx . 83. W hat is the value of c such that the line y − 2x 1 3 is tangent to the parabola y − cx 2 ? 84. T he graph of any quadratic function f sxd − ax 2 1 bx 1 c is a parabola. Prove that the average of the slopes of the tangent lines to the parabola at the endpoints of any interval f p, qg equals the slope of the tangent line at the midpoint of the interval.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
184
CHAPTER 3 Differentiation Rules
85. Let f sxd −
H
x2 if x < 2 mx 1 b if x . 2
(b) Show that the triangle formed by the tangent line and the coordinate axes always has the same area, no matter where P is located on the hyperbola. y
Find the values of m and b that make f differentiable everywhere.
xy=c
86. Find numbers a and b such that the given function t is differentiable at 1. tsxd −
87. Evaluate lim
xl1
H
ax 3 2 3x if x < 1 bx 2 1 2 if x . 1
x 1000 2 1 . x21
88. A tangent line is drawn to the hyperbola xy − c at a point P as shown in the figure. (a) Show that the midpoint of the line segment cut from this tangent line by the coordinate axes is P.
P x
0
89. D raw a diagram showing two perpendicular lines that intersect on the yaxis and are both tangent to the parabola y − x 2. Where do these lines intersect? 90. S ketch the parabolas y − x 2 and y − x 2 2 2x 1 2. Do you think there is a line that is tangent to both curves? If so, find its equation. If not, why not? 91. If c . 12, how many lines through the point s0, cd are normal lines to the parabola y − x 2 ? What if c < 12 ?
APPLIED PROJECT BUILDING A BETTER ROLLER COASTER
L¡
P
f
Susana Ortega / Shutterstock.com
Q
L™
Suppose you are asked to design the first ascent and drop for a new roller coaster. By studying photographs of your favorite coasters, you decide to make the slope of the ascent 0.8 and the slope of the drop 21.6. You decide to connect these two straight stretches y − L 1sxd and y − L 2 sxd with part of a parabola y − f sxd − a x 2 1 bx 1 c, where x and f sxd are measured in meters. For the track to be smooth there can’t be abrupt changes in direction, so you want the linear segments L 1 and L 2 to be tangent to the parabola at the transition points P and Q. (See the figure.) To simplify the equations, you decide to place the origin at P. 1. (a) Suppose the horizontal distance between P and Q is 30 m. Write equations in a, b, and c that will ensure that the track is smooth at the transition points. (b) Solve the equations in part (a) for a, b, and c to find a formula for f sxd. ; (c) Plot L 1, f , and L 2 to verify graphically that the transitions are smooth. (d) Find the difference in elevation between P and Q. 2. T he solution in Problem 1 might look smooth, but it might not feel smooth because the piecewise defined function [consisting of L 1sxd for x , 0, f sxd for 0 < x < 30, and L 2sxd for x . 30] doesn’t have a continuous second derivative. So you decide to improve the design by using a quadratic function qsxd − ax 2 1 bx 1 c only on the interval 3 < x < 27 and connecting it to the linear functions by means of two cubic functions: tsxd − kx 3 1 lx 2 1 mx 1 n 0 0, where s is measured in centimeters and t in seconds. (Take the positive direction to be downward.) (a) Find the velocity and acceleration at time t. (b) Graph the velocity and acceleration functions. (c) When does the mass pass through the equilibrium position for the first time? (d) How far from its equilibrium position does the mass travel? (e) When is the speed the greatest?
 
43. A ladder 6 m long rests against a vertical wall. Let be the angle between the top of the ladder and the wall and let x be the distance from the bottom of the ladder to the wall. If the bottom of the ladder slides away from the wall, how fast does x change with respect to when − y3?
sin , find t9sd and t99sd.
44. A n object with mass m is dragged along a horizontal plane by a force acting along a rope attached to the object. If the rope makes an angle with the plane, then the magnitude of the force is
34. (a) If f sxd − e cos x, find f 9sxd and f 99sxd. (b) Check to see that your answers to part (a) are reason; able by graphing f , f 9, and f 99. x
35. If tsd −
36. If f std − sec t, find f 0sy4d.
F−
37. (a) Use the Quotient Rule to differentiate the function f sxd −
x
x
tan x 2 1 sec x
(b) Simplify the expression for f sxd by writing it in terms of sin x and cos x, and then find f 9sxd. (c) Show that your answers to parts (a) and (b) are equivalent.
38. Suppose f sy3d − 4 and f 9sy3d − 22, and let tsxd − f sxd sin x and hsxd − scos xdyf sxd. Find (a) t9sy3d (b) h9sy3d 39–40 For what values of x does the graph of f have a horizontal tangent? 39. f sxd − x 1 2 sin x
40. f sxd − e x cos x
mg sin 1 cos
where is a constant called the coefficient of friction. (a) Find the rate of change of F with respect to . (b) When is this rate of change equal to 0 ? (c) If m − 20 kg and − 0.6, draw the graph of F as a ; function of and use it to locate the value of for which dFyd − 0. Is the value consistent with your answer to part (b)? 45–60 Find the limit. 45. lim
sin 5x 3x
46. lim
sin x sin x
47. lim
sin 3t sin t
48. lim
sin2 3x x
xl 0
tl0
xl 0
xl0
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.4 The Chain Rule
49. lim
sin x 2 sin x cos x x2
50. lim
1 2 sec x 2x
51. lim
tan 2x x
52. lim
sin tan 7
53. lim
sin 3x 5x 3 2 4x
54. lim
sin 3x sin 5x x2
55. lim
sin 1 tan
56. lim csc x sinssin xd
57. lim
cos 2 1 2 2
58. lim
sinsx 2 d x
60. lim
sinsx 2 1d x2 1 x 2 2
x l0
xl0
xl0
l 0
l0
59. lim
x l y4
xl0
l0
xl0
66. A semicircle with diameter PQ sits on an isosceles triangle PQR to form a region shaped like a twodimensional icecream cone, as shown in the figure. If Asd is the area of the semicircle and Bsd is the area of the triangle, find
1 2 tan x sin x 2 cos x
xl1
A(¨ ) P
d 99 ssin xd dx 99
62.
10 cm
10 cm ¨ R
67. T he figure shows a circular arc of length s and a chord of length d, both subtended by a central angle . Find
d 35 sx sin xd dx 35
lim
l 01
63. Find constants A and B such that the function y − A sin x 1 B cos x satisfies the differential equation y99 1 y9 2 2y − sin x.
d
1 . x 1 (b) Evaluate lim x sin . xl0 x (c) Illustrate parts (a) and (b) by graphing y − x sins1yxd. xl`
;
65. D ifferentiate each trigonometric identity to obtain a new (or familiar) identity. (a) tan x −
sin x 1 (b) sec x − cos x cos x
(c) sin x 1 cos x −
1 1 cot x csc x
s d s
¨
64. (a) Evaluate lim x sin
Q
B(¨ )
61–62 Find the given derivative by finding the first few derivatives and observing the pattern that occurs. 61.
Asd Bsd
lim
l 01
xl 0
xl0
199
; 68. Let f sxd −
x s1 2 cos 2x
.
(a) Graph f . What type of discontinuity does it appear to have at 0? (b) Calculate the left and right limits of f at 0. Do these values confirm your answer to part (a)?
3.4 The Chain Rule Suppose you are asked to differentiate the function Fsxd − sx 2 1 1
See Section 1.3 for a review of composite functions.
The differentiation formulas you learned in the previous sections of this chapter do not enable you to calculate F9sxd. Observe that F is a composite function. In fact, if we let y − f sud − su and let u − tsxd − x 2 1 1, then we can write y − Fsxd − f stsxdd, that is, F − f 8 t. We know how to differentiate both f and t, so it would be useful to have a rule that tells us how to find the derivative of F − f 8 t in terms of the derivatives of f and t.
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200
CHAPTER 3 Differentiation Rules
■ The Chain Rule It turns out that the derivative of the composite function f 8 t is the product of the derivatives of f and t. This fact is one of the most important of the differentiation rules and is called the Chain Rule. It seems plausible if we interpret derivatives as rates of change. Regard duydx as the rate of change of u with respect to x, dyydu as the rate of change of y with respect to u, and dyydx as the rate of change of y with respect to x. If u changes twice as fast as x and y changes three times as fast as u, then it seems reasonable that y changes six times as fast as x, and so we expect that dyydx is the product of dyydu and duydx . The Chain Rule If t is differentiable at x and f is differentiable at tsxd, then the composite function F − f 8 t defined by Fsxd − f stsxdd is differentiable at x and F9 is given by the product F9sxd − f 9s tsxdd ? t9sxd
1
In Leibniz notation, if y − f sud and u − tsxd are both differentiable functions, then dy dy du − dx du dx
2
Formula 2 is easy to remember because if we think of dyydu and duydx as quotients, then we could cancel du ; however, du has not been defined and duydx should not be considered as an actual quotient. James Gregory The first person o formulate the Chain Rule was the Scottish mathematician James Gregory (1638 –1675), who also designed the first p actical refle ting telescope. Gregory discovered the basic ideas of calculus at about the same time as Newton. He became the first rofessor of Mathe matics at the University of St. Andrews and later held the same position at the University of Edinburgh. But one year after accepting that position, he died at the age of 36.
COMMENTS ON THE PROOF OF THE CHAIN RULE Let Du be the change in u corresponding to a change of Dx in x, that is, Du − tsx 1 Dxd 2 tsxd Then the corresponding change in y is Dy − f su 1 Dud 2 f sud It is tempting to write dy Dy − lim Dxl 0 Dx dx
− lim
Dy Du Du Dx
− lim
Dy Du lim Du Dx l 0 Dx
− lim
Dy Du (Note that Du l 0 as Dx l 0 lim because t is continuous.) Du Dx l 0 Dx
−
3
Dx l 0
Dx l 0
Du l 0
dy du du dx
The only flaw in this reasoning is that in (3) it might happen that Du − 0 (even when Dx ± 0) and, of course, we can’t divide by 0. Nonetheless, this reasoning does at least suggest that the Chain Rule is true. A full proof of the Chain Rule is given at the end of this section. ■ Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.4 The Chain Rule
201
EXAMPLE 1 Find F9sxd if Fsxd − sx 2 1 1. SOLUTION 1 (using Formula 1): At the beginning of this section we expressed F as Fsxd − s f 8 tdsxd − f stsxdd where f sud − su and tsxd − x 2 1 1. Since f 9sud − 12 u21y2 −
1 2 su
and t9sxd − 2x
F9sxd − f 9stsxdd t9sxd
we have
−
1 2 sx 1 1 2
2x −
x sx 1 1 2
SOLUTION 2 (using Formula 2): If we let u − x 2 1 1 and y − su , then
dy du 1 1 x − s2xd − s2xd − 2 2 du dx 2 su 2 sx 1 1 sx 1 1
F9sxd −
■
When using Formula 2 we should bear in mind that dyydx refers to the derivative of y when y is considered as a function of x (the derivative of y with respect to x), whereas dyydu refers to the derivative of y when considered as a function of u (the derivative of y with respect to u). For instance, in Example 1, y can be considered as a function of x ( y − s x 2 1 1 ) and also as a function of u ( y − su ). Note that dy x dy 1 − F9sxd − whereas − f 9sud − 2 1 1 dx du 2 su sx NOTE In using the Chain Rule we work from the outside to the inside. Formula 1 says that we differentiate the outer function f [at the inner function tsxd] and then we multiply by the derivative of the inner function.
d dx
f
stsxdd
outer function
evaluated at inner function
f9
stsxdd
derivative of outer function
evaluated at inner function
−
t9sxd
derivative of inner function
EXAMPLE 2 Differentiate (a) y − sinsx 2 d and (b) y − sin2x. SOLUTION (a) If y − sinsx 2 d, then the outer function is the sine function and the inner function is the squaring function, so the Chain Rule gives dy d − dx dx
sin
sx 2 d
outer function
evaluated at inner function
− 2x cossx 2 d
cos
sx 2 d
derivative of outer function
evaluated at inner function
−
2x derivative of inner function
(b) Note that sin2x − ssin xd2. Here the outer function is the squaring function and the inner function is the sine function. So dy d − ssin xd2 dx dx inner function
See Reference Page 2 or Appendix D.
−
2
ssin xd
cos x
derivative evaluatedevaluated derivative derivative derivative derivative derivative evaluated evaluated derivative derivative of outerofofof at inner atatinner outer outer outer atinner inner of inner ofofof inner inner inner functionfunction function function function function function function function function function function
The answer can be left as 2 sin x cos x or written as sin 2x (by a trigonometric identity known as the doubleangle formula). ■
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
202
CHAPTER 3 Differentiation Rules
In Example 2(a) we combined the Chain Rule with the rule for differentiating the sine function. In general, if y − sin u, where u is a differentiable function of x, then, by the Chain Rule, dy dy du du − − cos u dx du dx dx d du ssin ud − cos u dx dx
Thus
In a similar fashion, all of the formulas for differentiating trigonometric functions can be combined with the Chain Rule. Let’s make explicit the special case of the Chain Rule where the outer function f is a power function. If y − ftsxdg n, then we can write y − f sud − u n where u − tsxd. By using the Chain Rule and then the Power Rule, we get dy dy du du − − nu n21 − nftsxdg n21 t9sxd dx du dx dx
4 The Power Rule Combined with the Chain Rule If n is any real number and u − tsxd is differentiable, then d du su n d − nu n21 dx dx d ftsxdg n − n ftsxdg n21 t9sxd dx
Alternatively,
Notice that the derivative we found in Example 1 could be calculated by taking n − 12 in Rule 4.
EXAMPLE 3 Differentiate y − sx 3 2 1d100. SOLUTION Taking u − tsxd − x 3 2 1 and n − 100 in (4), we have dy d d − sx 3 2 1d100 − 100sx 3 2 1d99 sx 3 2 1d dx dx dx
− 100sx 3 2 1d99 3x 2 − 300x 2sx 3 2 1d99
EXAMPLE 4 Find f 9sxd if f sxd − SOLUTION First rewrite f : Thus
1 sx 2 1 x 1 1 3
■
.
f sxd − sx 2 1 x 1 1d21y3
f 9sxd − 213 sx 2 1 x 1 1d24y3
d sx 2 1 x 1 1d dx
− 213 sx 2 1 x 1 1d24y3s2x 1 1d
■
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SECTION 3.4 The Chain Rule
203
EXAMPLE 5 Find the derivative of the function tstd −
S D t22 2t 1 1
9
SOLUTION Combining the Power Rule, Chain Rule, and Quotient Rule, we get
S D S D S D
t9std − 9
t22 2t 1 1
8
d dt
t22 2t 1 1
8
−9
s2t 1 1d 1 2 2st 2 2d 45st 2 2d8 − 2 s2t 1 1d s2t 1 1d10
t22 2t 1 1
■
EXAMPLE 6 Differentiate y − s2x 1 1d5sx 3 2 x 1 1d4. SOLUTION In this example we must use the Product Rule before using the Chain Rule: dy d d − s2x 1 1d5 sx 3 2 x 1 1d4 1 sx 3 2 x 1 1d4 s2x 1 1d5 dx dx dx
The graphs of the functions y and y9 in Example 6 are shown in Figure 1. Notice that y9 is large when y increases rapidly and y9 − 0 when y has a horizontal tangent. So our answer appears to be reasonable.
− s2x 1 1d5 4sx 3 2 x 1 1d3
d sx 3 2 x 1 1d dx
1 sx 3 2 x 1 1d4 5s2x 1 1d4
10
yª
d s2x 1 1d dx
− 4s2x 1 1d5sx 3 2 x 1 1d3s3x 2 2 1d 1 5sx 3 2 x 1 1d4s2x 1 1d4 2
_2
1
y _10
FIGURE 1
Noticing that each term has the common factor 2s2x 1 1d4sx 3 2 x 1 1d3, we could factor it out and write the answer as
dy − 2s2x 1 1d4sx 3 2 x 1 1d3s17x 3 1 6x 2 2 9x 1 3d dx
■
EXAMPLE 7 Differentiate y − e sin x. SOLUTION Here the inner function is tsxd − sin x and the outer function is the exponential function f sxd − e x. So, by the Chain Rule, More generally, the Chain Rule gives d u du se d − e u dx dx
dy d d − se sin x d − e sin x ssin xd − e sin x cos x dx dx dx
■
The reason for the name “Chain Rule” becomes clear when we make a longer chain by adding another link. Suppose that y − f sud, u − tsxd, and x − hstd where f , t, and h are differentiable functions. Then, to compute the derivative of y with respect to t, we use the Chain Rule twice: dy dy dx dy du dx − − dt dx dt du dx dt
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
204
CHAPTER 3 Differentiation Rules
EXAMPLE 8 If f sxd − sinscosstan xdd, then f 9sxd − cosscosstan xdd
d cosstan xd dx
− cosscosstan xdd f2sinstan xdg
d stan xd dx
− 2cosscosstan xdd sinstan xd sec2x Notice that we used the Chain Rule twice.
■
EXAMPLE 9 Differentiate y − e sec 3. SOLUTION The outer function is the exponential function, the middle function is the secant function, and the inner function is the tripling function. So we have dy d − e sec 3 ssec 3d d d d s3d d − 3e sec 3 sec 3 tan 3 − e sec 3 sec 3 tan 3
■
■ Derivatives of General Exponential Functions We can use the Chain Rule to differentiate an exponential function with any base b . 0. Recall from Equation 1.5.10 that we can write b x − e sln bdx and then the Chain Rule gives d d d sb x d − se sln bdx d − e sln bdx [sln bdx] dx dx dx − e sln bdx sln bd − b x ln b because ln b is a constant. So we have the formula Don’t confuse Formula 5 (where x is the exponent) with the Power Rule (where x is the base):
d sb x d − b x ln b dx
5
d sx n d − nx n21 dx
EXAMPLE 10 Find the derivative of each of the functions. 2 hsxd − 5 x (a) tsxd − 2 x (b) SOLUTION (a) We use Formula 5 with b − 2: t9sxd −
d s2 x d − 2 x ln 2 dx
This is consistent with the estimate d s2 x d < s0.693d2 x dx we gave in Section 3.1 because ln 2 < 0.693147.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 3.4 The Chain Rule
205
(b) The outer function is an exponential function and the inner function is the squaring function, so we use Formula 5 and the Chain Rule to get
h9sxd −
d d ( 5 x 2) − 5 x 2 ln 5 ? sx 2d − 2x ? 5 x 2 ln 5 dx dx
■
■ How to Prove the Chain Rule Recall that if y − f sxd and x changes from a to a 1 Dx, we define the increment of y as Dy − f sa 1 Dxd 2 f sad According to the definition of a derivative, we have lim
Dx l 0
Dy − f 9sad Dx
So if we denote by « the difference between DyyDx and f 9sad, we obtain lim « − lim
Dx l 0
But
«−
Dx l 0
S
D
Dy 2 f 9sad − f 9sad 2 f 9sad − 0 Dx
Dy 2 f 9sad Dx
?
Dy − f 9sad Dx 1 « Dx
If we define « to be 0 when Dx − 0, then « becomes a continuous function of Dx. Thus, for a differentiable function f, we can write 6
Dy − f 9sad Dx 1 « Dx
where
« l 0 as Dx l 0
and « is a continuous function of Dx. This property of differentiable functions is what enables us to prove the Chain Rule. PROOF OF THE CHAIN RULE Suppose u − tsxd is differentiable at a and y − f sud is differentiable at b − tsad. If Dx is an increment in x and Du and Dy are the corresponding increments in u and y, then we can use Equation 6 to write 7
Du − t9sad Dx 1 «1 Dx − f t9sad 1 «1 g Dx
where «1 l 0 as Dx l 0. Similarly 8
Dy − f 9sbd Du 1 «2 Du − f f 9sbd 1 «2 g Du
where «2 l 0 as Du l 0. If we now substitute the expression for Du from Equation 7 into Equation 8, we get Dy − f f 9sbd 1 «2 gf t9sad 1 «1 g Dx so
Dy − f f 9sbd 1 «2 gf t9sad 1 «1 g Dx
As Dx l 0, Equation 7 shows that Du l 0. Taking the limit as Dx l 0 , we get dy Dy − lim − lim f f 9sbd 1 «2 gft9sad 1 «1 g Dx l 0 Dx Dx l 0 dx − f 9sbd t9sad − f 9stsadd t9sad This proves the Chain Rule.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
■
206
CHAPTER 3 Differentiation Rules
3.4 Exercises 1–6 Write the composite function in the form f s tsxdd. [Identify the inner function u − tsxd and the outer function y − f sud.] Then find the derivative dyydx.
47. f sxd − esin
2 sx 2d
48. y − 23
4x
2
49. y − s3cossx d 2 1d4
1. y − s5 2 x 4d3
2. y − sx 3 1 2
50. y − sins 1 tans 1 cos dd
3. y − sinscos xd
4. y − tansx d
51. y − cos ssinstan xd
5. y − esx
3 ex 1 1 6. y − s
2
52. y − sin3scossx 2 dd
53–56 Find y9 and y 99. 7–52 Find the derivative of the function. 7. f sxd − s2x 2 5x 1 4d 3
2
5
9. f sxd − s5x 1 1
8. f sxd − sx 1 3x 2 xd 5
2
1
10. f sxd −
3 x2 2 1 s
S D
1 11. tstd − s2t 1 1d2
12. Fstd −
13. f sd − coss d
14. tsd − cos
2
15. tsxd − e
sx
18. f std − t sin t
20. Asrd − sr ? e r
19. f std − e at sin bt 22. Gszd − s1 2 4zd2sz 2 1 1
27. tsud −
S
u3 2 1 u3 1 1
56. y − e e
x
57. y − 2 x, s0, 1d
58. y − s1 1 x 3 , s2, 3d
59. y − sinssin xd, s, 0d
60. y − xe 2x , s0, 0d
2
D
S D
26. f std − 2 t
8
 
62. (a) The curve y − x ys2 2 x 2 is called a bulletnose curve. Find an equation of the tangent line to this curve at the point s1, 1d. (b) Illustrate part (a) by graphing the curve and the tangent ; line on the same screen.
5
1 24. y − x 1 x
x x11
25. y − e tan
55. y − scos x
3
61. (a) Find an equation of the tangent line to the curve y − 2ys1 1 e2x d at the point s0, 1d. (b) Illustrate part (a) by graphing the curve and the tangent ; line on the same screen.
2 11
21. Fsxd − s4x 1 5d 3sx 2 2 2x 1 5d4
Î
54. y − (1 1 sx )
16. y − 5
2 23x
23. y −
53. y − cosssin 3d
57–60 Find an equation of the tangent line to the curve at the given point.
4
2
x 22x
17. y − x e
1 2t 1 1
50
28. sstd −
3
Î
1 1 sin t 1 1 cos t
29. rstd − 10 2st
30. f szd − e zysz21d
sr 2 2 1d 3 31. Hsrd − s2r 1 1d 5
32. Jsd − tan snd
33. Fstd − e t sin 2t
34. Fstd −
35. Gsxd − 4 Cyx
36. Us yd −
2
t2 st 1 1 3
S D y4 1 1 y2 1 1
5
37. f sxd − sin x coss1 2 x 2 d 38. tsxd − e2x cossx 2 d 39. Fstd − tan s1 1 t 2
40. Gszd − s1 1 cos2zd3
41. y − sin2sx 2 1 1d
42. y − e sin 2x 1 sinse 2x d
ex 43. tsxd − sin 1 1 ex
44. f std − e st 2 1
45. f std − tanssecscos tdd
46. y − sx 1 sx 1 s x
S D
1yt
2
63. (a) If f sxd − x s2 2 x 2 , find f 9sxd. (b) Check to see that your answer to part (a) is reasonable by ; comparing the graphs of f and f 9. ; 64. The function f sxd − sinsx 1 sin 2xd, 0 < x < , arises in applications to frequency modulation (FM) synthesis. (a) Use a graph of f produced by a calculator or computer to make a rough sketch of the graph of f 9. (b) Calculate f 9sxd and use this expression, with a calculator or computer, to graph f 9. Compare with your sketch in part (a). 65. F ind all points on the graph of the function f sxd − 2 sin x 1 sin2x at which the tangent line is horizontal. 66. A t what point on the curve y − s1 1 2x is the tangent line perpendicular to the line 6x 1 2y − 1? 67. If Fsxd − f stsxdd, where f s22d − 8, f 9s22d − 4, f 9s5d − 3, ts5d − 22, and t9s5d − 6, find F9s5d. 68. If hsxd − s4 1 3f sxd , where f s1d − 7 and f 9s1d − 4, find h9s1d.
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SECTION 3.4 The Chain Rule
69. A table of values for f , t, f 9, and t9 is given.
x
f sxd
tsxd
f 9sxd
t9sxd
1 2 3
3 1 7
2 8 2
4 5 7
6 7 9
(a) If hsxd − f stsxdd, find h9s1d. (b) If Hsxd − ts f sxdd, find H9s1d.
70. Let f and t be the functions in Exercise 69. (a) If Fsxd − f s f sxdd, find F9s2d. (b) If Gsxd − tstsxdd, find G9s3d. 71. If f and t are the functions whose graphs are shown, let usxd − f s tsxdd, vsxd − ts f sxdd, and w sxd − ts tsxdd. Find each derivative, if it exists. If it does not exist, explain why. (a) u9s1d (b) v9s1d (c) w9s1d y
207
74. Suppose f is differentiable on R and is a real number. Let Fsxd − f sx d and Gsxd − f f sxdg . Find expressions for (a) F9sxd and (b) G9sxd. 75. Suppose f is differentiable on R. Let Fsxd − f se x d and Gsxd − e f sxd. Find expressions for (a) F9sxd and (b) G9sxd. 76. Let tsxd − e cx 1 f sxd and hsxd − e kx f sxd, where f s0d − 3, f 9s0d − 5, and f 99s0d − 22. (a) Find t9s0d and t99s0d in terms of c. (b) In terms of k, find an equation of the tangent line to the graph of h at the point where x − 0. 77. Let rsxd − f s tshsxddd, where hs1d − 2, ts2d − 3, h9s1d − 4, t9s2d − 5, and f 9s3d − 6. Find r9s1d. 78. If t is a twice differentiable function and f sxd − x tsx 2 d, find f 99 in terms of t, t9, and t99. 79. I f Fsxd − f s3f s4 f sxddd, where f s0d − 0 and f 9s0d − 2, find F9s0d. 80. If Fsxd − f sx f sx f sxddd, where f s1d − 2, f s2d − 3, f 9s1d − 4, f 9s2d − 5, and f 9s3d − 6, find F9s1d. 81. S how that the function y − e 2x sA cos 3x 1 B sin 3xd satisfies the differential equation y99 2 4y9 1 13y − 0.
f
82. F or what values of r does the function y − e rx satisfy the differential equation y99 2 4y9 1 y − 0 ?
g 1
83. Find the 50th derivative of y − cos 2x.
0
x
1
72. If f is the function whose graph is shown, let hsxd − f s f sxdd and tsxd − f sx 2 d. Use the graph of f to estimate the value of each derivative. (a) h9s2d (b) t9s2d y
1 1
85. T he displacement of a particle on a vibrating string is given by the equation sstd − 10 1 14 sins10td where s is measured in centimeters and t in seconds. Find the velocity of the particle after t seconds. 86. I f the equation of motion of a particle is given by s − A cosst 1 d, the particle is said to undergo simple harmonic motion. (a) Find the velocity of the particle at time t. (b) When is the velocity 0 ?
y=ƒ
0
84. Find the 1000th derivative of f sxd − xe2x.
x
73. If tsxd − sf sxd , where the graph of f is shown, evaluate t9s3d. y
87. A Cepheid variable star is a star whose brightness alternately increases and decreases. The most easily visible such star is Delta Cephei, for which the interval between times of maximum brightness is 5.4 days. The average brightness of this star is 4.0 and its brightness changes by 60.35. In view of these data, the brightness of Delta Cephei at time t, where t is mea sured in days, has been modeled by the function
S D
Bstd − 4.0 1 0.35 sin f
1 0
1
x
2t 5.4
(a) Find the rate of change of the brightness after t days. (b) Find, correct to two decimal places, the rate of increase after one day.
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208
CHAPTER 3 Differentiation Rules
93. A particle moves along a straight line with displacement sstd, velocity vstd, and acceleration astd. Show that
88. I n Example 1.3.4 we arrived at a model for the length of daylight (in hours) in Philadelphia on the t th day of the year:
F
Lstd − 12 1 2.8 sin
2 st 2 80d 365
G
Use this model to compare how the number of hours of daylight is increasing in Philadelphia on March 21 st − 80d and May 21 st − 141d.
astd − vstd
Explain the difference between the meanings of the derivatives dvydt and dvyds. 94. The table gives the US population from 1790 to 1860.
he motion of a spring that is subject to a frictional force or ; 89. T a damping force (such as a shock absorber in a car) is often modeled by the product of an exponential function and a sine or cosine function. Suppose the equation of motion of a point on such a spring is sstd − 2e21.5t sin 2t where s is measured in centimeters and t in seconds. Find the velocity after t seconds and graph both the position and velocity functions for 0 < t < 2. 90. U nder certain circumstances a rumor spreads according to the equation 1 pstd − 1 1 ae 2k t
;
where pstd is the proportion of the population that has heard the rumor at time t and a and k are positive constants. [In Section 9.4 we will see that this is a reasonable equation for pstd.] (a) Find lim t l ` pstd and interpret your answer. (b) Find the rate of spread of the rumor. (c) Graph p for the case a − 10, k − 0.5 with t measured in hours. Use the graph to estimate how long it will take for 80% of the population to have heard the rumor.
Population
Year
Population
1790 1800 1810 1820
3,929,000 5,308,000 7,240,000 9,639,000
1830 1840 1850 1860
12,861,000 17,063,000 23,192,000 31,443,000
(a) Fit an exponential function to the data. Graph the data points and the exponential model. How good is the fit? (b) Estimate the rates of population growth in 1800 and 1850 by averaging slopes of secant lines. (c) Use the exponential model in part (a) to estimate the rates of growth in 1800 and 1850. Compare these estimates with the ones in part (b). (d) Use the exponential model to predict the population in 1870. Compare with the actual population of 38,558,000. Can you explain the discrepancy?
96. U se the Chain Rule and the Product Rule to give an alter native proof of the Quotient Rule. [Hint: Write f sxdytsxd − f sxdf tsxdg 21.] 97. U se the Chain Rule to show that if is measured in degrees, then d ssin d − cos d 180
Cstd − 0.00225te 20.0467t
(This gives one reason for the convention that radian measure is always used when dealing with trigonometric functions in calculus: the differentiation formulas would not be as simple if we used degree measure.)
where t is measured in minutes after consumption and C is measured in gydL. (a) How rapidly was the BAC increasing after 10 minutes? (b) How rapidly was it decreasing half an hour later?
 
98. (a) Write x − sx 2 and use the Chain Rule to show that
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after Oral Administration in the Fasting State,” Journal of Pharmacokinetics and Biopharmaceutics 5 (1977): 207–24.
92. A ir is being pumped into a spherical weather balloon. At any time t, the volume of the balloon is Vstd and its radius is rstd. (a) What do the derivatives dVydr and dVydt represent? (b) Express dVydt in terms of drydt.
Year
95. Use the Chain Rule to prove the following. (a) The derivative of an even function is an odd function. (b) The derivative of an odd function is an even function.
91. T he average blood alcohol concentration (BAC) of eight male subjects was measured after consumption of 15 mL of ethanol (corresponding to one alcoholic drink). The resulting data were modeled by the concentration function
dv ds
d x − dx
 


x x
 
(b) If f sxd − sin x , find f 9sxd and sketch the graphs of f and f 9. Where is f not differentiable? (c) If tsxd − sin x , find t9sxd and sketch the graphs of t and t9. Where is t not differentiable?
 
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SECTION 3.5 Implicit Differentiation
99. Let c be the xintercept of the tangent line to the curve y − b x sb . 0, b ± 1d at the point sa, b a d. Show that the distance between the points sa, 0d and sc, 0d is the same for all values of a. y
F9sxd − f 9s tshsxdd ? t9shsxdd ? h9sxd 102. If F − f + t, where f and t are twice differentiable functions, use the Chain Rule and the Product Rule to show that the second derivative of F is given by
(a, b a)
c
100. On every exponential curve y − b x sb . 0, b ± 1d, there is exactly one point sx 0, y 0d at which the tangent line to the curve passes through the origin. Show that in every case, y0 − e. [Hint: You may wish to use Formula 1.5.10.] 101. If F − f + t + h , where f , t, and h are differentiable functions, use the Chain Rule to show that
y=b x
0
209
x
a
F 0sxd − f 0s tsxdd ? [ t9sxd] 2 1 f 9s tsxdd ? t 0sxd
APPLIED PROJECT WHERE SHOULD A PILOT START DESCENT? y
An approach path for an aircraft landing is shown in the figure and satisfies the following conditions:
y=P(x)
0
h
x
(i) The cruising altitude is h when descent starts at a horizontal distance , from touchdown at the origin.
(ii) The pilot must maintain a constant horizontal speed v throughout descent.
(iii) The absolute value of the vertical acceleration should not exceed a constant k (which is much less than the acceleration due to gravity).
1. Find a cubic polynomial Psxd − ax 3 1 bx 2 1 cx 1 d that satisfies condition (i) by imposing suitable conditions on Psxd and P9sxd at the start of descent and at touchdown. 2. U se conditions (ii) and (iii) to show that 6h v 2 5 .
y 5 1 3x 2 y 2 1 5x 4 − 12 for which it is impossible to find an expression for y in terms of x.
EXAMPLE 3 Find y9 if sinsx 1 yd − y 2 cos x. SOLUTION Differentiating implicitly with respect to x and remembering that y is a function of x, we get cossx 1 yd s1 1 y9d − y 2s2sin xd 1 scos xds2yy9d (Note that we have used the Chain Rule on the left side and the Product Rule and Chain Rule on the right side.) If we collect the terms that involve y9, we get
2
cossx 1 yd 1 y 2 sin x − s2y cos xdy9 2 cossx 1 yd y9 _2
So
2
y9 −
y 2 sin x 1 cossx 1 yd 2y cos x 2 cossx 1 yd
Figure 6, drawn by a computer, shows part of the curve sinsx 1 yd − y 2 cos x. As a check on our calculation, notice that y9 − 21 when x − y − 0 and it appears from the graph that the slope is approximately 21 at the origin. ■ _2
Figures 7, 8, and 9 show three more curves produced by a computer. In Exercises 45–46 you will have an opportunity to create and examine unusual curves of this nature.
FIGURE 6 4
_4
15
4
_15
_4
12
15
_12
_15
FIGURE 7 sx 2 2 1dsx 2 2 4dsx 2 2 9d − y 2 s y 2 2 4ds y 2 2 9d
12
_12
FIGURE 8 cossx 2 sin yd − sins y 2 sin xd
FIGURE 9 sinsxyd − sin x 1 sin y
■ Second Derivatives of Implicit Functions The following example shows how to find the second derivative of a function that is defined implicitly.
EXAMPLE 4 Find y99 if x 4 1 y 4 − 16. SOLUTION Differentiating the equation implicitly with respect to x, we get 4x 3 1 4y 3 y9 − 0 Solving for y9 gives 3
y9 − 2
x3 y3
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214
CHAPTER 3 Differentiation Rules
To find y99 we differentiate this expression for y9 using the Quotient Rule and remembering that y is a function of x:
S D
d x3 y 3 sdydxdsx 3 d 2 x 3 sdydxdsy 3 d 2 3 −2 dx y sy 3 d2 3 2 3 2 y 3x 2 x s3y y9d −2 y6
y99 −
If we now substitute Equation 3 into this expression, we get
S D
3x 2 y 3 2 3x 3 y 2 2 y99 − 2
x3 y3
y6 3sx 2 y 4 1 x 6 d 3x 2sy 4 1 x 4 d −2 −2 7 y y7
But the values of x and y must satisfy the original equation x 4 1 y 4 − 16. So the answer simplifies to 3x 2s16d x2 y99 − 2 − 248 7 7 y y y
Figure 10 shows the graph of the curve x 4 1 y 4 − 16 of Example 4. Notice that it’s a stretched and flattened version of the circle x 2 1 y 2 − 4. For this reason it’s sometimes called a fat circle. It starts out very steep on the left but quickly becomes very flat. This can be seen from the expression y9 − 2
2
x $+y$ =16
0
SD
x3 x −2 y3 y
■
2 x
3
FIGURE 10
3.5 Exercises 1–4 (a) Find y9 by implicit differentiation. (b) Solve the equation explicitly for y and differentiate to get y9 in terms of x. (c) Check that your solutions to parts (a) and (b) are consistent by substituting the expression for y into your solution for part (a). 1. 5x 2 2 y 3 − 7
2. 6x 4 1 y 5 − 2x
3. sx 1 sy − 1
4.
2 1 2 −4 x y
9.
x2 − y 2 1 1 x1y
10. xe y − x 2 y
11. sin x 1 cos y − 2x 2 3y
12. e x sin y − x 1 y
13. sinsx 1 yd − cos x 1 cos y
14. tansx 2 yd − 2x y 3 1 1
15. y cos x − x 2 1 y 2
16. sinsxyd − cossx 1 yd
17. 2xe 1 ye − 3
18. sin x cos y − x 2 2 5y
19. sx 1 y − x 4 1 y 4
20. xy − sx 2 1 y 2
21. e xyy − x 2 y
22. cossx 2 1 y 2 d − xe y
y
x
5–22 Find dyydx by implicit differentiation. 5. x 2 2 4xy 1 y 2 − 4
6. 2x 2 1 xy 2 y 2 − 2
23. If f sxd 1 x 2 f f sxdg 3 − 10 and f s1d − 2, find f 9s1d.
7. x 4 1 x 2 y 2 1 y 3 − 5
8. x 3 2 xy 2 1 y 3 − 1
24. If tsxd 1 x sin tsxd − x 2, find t9s0d.
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SECTION 3.5 Implicit Differentiation
25–26 Regard y as the independent variable and x as the dependent variable and use implicit differentiation to find dxydy. 25. x 4y 2 2 x 3y 1 2xy 3 − 0
26. y sec x − x tan y
27–36 Use implicit differentiation to find an equation of the tangent line to the curve at the given point. 27. ye sin x − x cos y, s0, 0d 28. tansx 1 yd 1 secsx 2 yd − 2, sy8, y8d 29. x 2y3 1 y 2y3 − 4, 30. y 2s6 2 xd − x 3,
(23 s3, 1) (astroid) (2, s2 ) (cissoid of Diocles)
31. x 2 2 xy 2 y 2 − 1, s2, 1d (hyperbola) 32. x 2 1 2xy 1 4y 2 − 12, s2, 1d (ellipse) 33. x 2 1 y 2 − s2x 2 1 2y 2 2 xd 2,
(0, 12 ) (cardioid)
y
215
37. (a) The curve with equation y 2 − 5x 4 2 x 2 is called a kampyle of Eudoxus. Find an equation of the tangent line to this curve at the point s1, 2d. (b) Illustrate part (a) by graphing the curve and the tangent ; line on a common screen. (Graph the implicitly defined curve if possible, or you can graph the upper and lower halves separately.) 38. (a) The curve with equation y 2 − x 3 1 3x 2 is called the Tschirnhausen cubic. Find an equation of the tangent line to this curve at the point s1, 22d. (b) At what points does this curve have horizontal tangents? (c) Illustrate parts (a) and (b) by graphing the curve and the ; tangent lines on a common screen. 39–42 Find y99 by implicit differentiation. Simplify where possible. 39. x 2 1 4y 2 − 4
40. x 2 1 xy 1 y 2 − 3
41. sin y 1 cos x − 1
42. x 3 2 y 3 − 7
43. If xy 1 e y − e, find the value of y99 at the point where x − 0. x
34. x 2 y 2 − s y 1 1d 2 s4 2 y 2 d, (conchoid of Nicomedes)
44. If x 2 1 xy 1 y 3 − 1, find the value of y999 at the point where x − 1.
(2 s3, 1)
ys y 2 2 1ds y 2 2d − xsx 2 1dsx 2 2d
y
At how many points does this curve have horizontal tangents? Estimate the xcoordinates of these points. (b) Find equations of the tangent lines at the points (0, 1) and (0, 2). (c) Find the exact xcoordinates of the points in part (a). (d) Create even more fanciful curves by modifying the equation in part (a).
x
0
35. 2sx 2 1 y 2 d2 − 25sx 2 2 y 2 d, s3, 1d (lemniscate)
x
0
36. y s y 2 4d − x sx 2 5d, s0, 22d (devil’s curve) 2
2
; 46. (a) The curve with equation 2y 3 1 y 2 2 y 5 − x 4 2 2x 3 1 x 2
y
2
anciful shapes can be created by using software that can ; 45. F graph implicitly defined curves. (a) Graph the curve with equation
2
has been likened to a bouncing wagon. Graph this curve and discover why. (b) At how many points does this curve have horizontal tangent lines? Find the xcoordinates of these points. 47. F ind the points on the lemniscate in Exercise 35 where the tangent is horizontal. 48. S how by implicit differentiation that the tangent line to the ellipse
y
x
x2 y2 −1 2 1 a b2 at the point sx 0 , y 0 d has equation x0 x y0 y 1 2 −1 a2 b
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
216
CHAPTER 3 Differentiation Rules
49. Find an equation of the tangent line to the hyperbola x2 y2 2 2 −1 2 a b at the point sx 0 , y 0 d. 50. Show that the sum of the x and yintercepts of any tangent line to the curve sx 1 sy − sc is equal to c. 51. S how, using implicit differentiation, that any tangent line at a point P to a circle with center O is perpendicular to the radius OP. 52. T he Power Rule can be proved using implicit differentiation for the case where n is a rational number, n − pyq, and y − f sxd − x n is assumed beforehand to be a differentiable function. If y − x pyq, then y q − x p. Use implicit differentiation to show that p s pyqd21 y9 − x q 53–56 Orthogonal Trajectories Two curves are orthogonal if their tangent lines are perpendicular at each point of intersection. Show that the given families of curves are orthogonal trajectories of each other; that is, every curve in one family is orthogonal to every curve in the other family. Sketch both families of curves on the same axes. 2
2
60. (a) Use implicit differentiation to find y9 if x 2 1 xy 1 y 2 1 1 − 0 ;
(b) Plot the curve in part (a). What do you see? Prove that what you see is correct. (c) In view of part (b), what can you say about the expression for y9 that you found in part (a)?
61. T he equation x 2 2 xy 1 y 2 − 3 represents a “rotated ellipse,” that is, an ellipse whose axes are not parallel to the coordinate axes. Find the points at which this ellipse crosses the xaxis and show that the tangent lines at these points are parallel. 62. (a) Where does the normal line to the ellipse x 2 2 xy 1 y 2 − 3 at the point s21, 1d intersect the ellipse a second time? (b) Illustrate part (a) by graphing the ellipse and the ; normal line. 63. F ind all points on the curve x 2 y 2 1 xy − 2 where the slope of the tangent line is 21. 64. F ind equations of both the tangent lines to the ellipse x 2 1 4y 2 − 36 that pass through the point s12, 3d. 65. Use implicit differentiation to find dyydx for the equation
2
53. x 1 y − r , ax 1 by − 0
x − y 2 1 1 y ± 0 y
54. x 2 1 y 2 − ax, x 2 1 y 2 − by 55. y − cx 2, x 2 1 2y 2 − k 3
2
and for the equivalent equation
2
56. y − ax , x 1 3y − b 57. S how that the ellipse x 2ya 2 1 y 2yb 2 − 1 and the hyperbola x 2yA2 2 y 2yB 2 − 1 are orthogonal trajectories if A2 , a 2 and a 2 2 b 2 − A2 1 B 2 (so the ellipse and hyperbola have the same foci). 58. F ind the value of the number a such that the families of curves y − sx 1 cd21 and y − asx 1 kd1y3 are orthogonal trajectories. 59. The van der Waals equation for n moles of a gas is
S
D
n 2a P 1 2 sV 2 nbd − nRT V
where P is the pressure, V is the volume, and T is the temperature of the gas. The constant R is the universal gas constant and a and b are positive constants that are characteristic of a particular gas. (a) If T remains constant, use implicit differentiation to find dVydP. (b) Find the rate of change of volume with respect to pressure of 1 mole of carbon dioxide at a volume of V − 10 L and a pressure of P − 2.5 atm. Use a − 3.592 L2atmymole 2 and b − 0.04267 Lymole.
x − y 3 1 y y ± 0 Show that although the expressions you get for dyydx look different, they agree for all points that satisfy the given equation. 66. The Bessel function of order 0, y − J sxd, satisfies the differential equation xy99 1 y9 1 xy − 0 for all values of x and its value at 0 is J s0d − 1. (a) Find J9s0d. (b) Use implicit differentiation to find J99s0d. 67. T he figure shows a lamp located three units to the right of the yaxis and a shadow created by the elliptical region x 2 1 4y 2 < 5. If the point s25, 0d is on the edge of the shadow, how far above the xaxis is the lamp located? y
? _5
0
≈+4¥=5
3
x
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SECTION 3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
DISCOVERY PROJECT
;
217
FAMILIES OF IMPLICIT CURVES
In this project you will explore the changing shapes of implicitly defined curves as you vary the constants in a family, and determine which features are common to all members of the family. 1. Consider the family of curves y 2 2 2x 2 sx 1 8d − c fs y 1 1d2 s y 1 9d 2 x 2 g (a) By graphing the curves with c − 0 and c − 2, determine how many points of intersection there are. (You might have to zoom in to find all of them.) (b) Now add the curves with c − 5 and c − 10 to your graphs in part (a). What do you notice? What about other values of c ? 2. (a) Graph several members of the family of curves x 2 1 y 2 1 cx 2 y 2 − 1 Describe how the graph changes as you change the value of c. (b) What happens to the curve when c − 21? Describe what appears on the screen. Can you prove it algebraically? (c) Find y9 by implicit differentiation. For the case c − 21, is your expression for y9 consistent with what you discovered in part (b)?
3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
In this section we use implicit differentiation to find derivatives of logarithmic functions and of inverse trigonometric functions.
■ Derivatives of Logarithmic Functions In Appendix F we prove that if f is a onetoone differentiable function, then its inverse function f 21 is also differentiable, except where its tangents are vertical. This is plau sible because, geometrically, we can think of a differentiable function as one whose graph has no corner or cusp. We obtain the graph of f 21 by reflecting the graph of f about the line y − x, so the graph of f 21 has no corner or cusp either. (Note that if f has a horizontal tangent at a point, then f 21 has a vertical tangent at the corresponding reflected point and so f 21 is not differentiable there.) Because the logarithmic function y − log b x is the inverse of the exponential function y − b x, which we know is differentiable from Section 3.1, it follows that the logarithmic function is also differentiable. We now state and prove the formula for the derivative of a logarithmic function. 1
d 1 slog b xd − dx x ln b
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218
CHAPTER 3 Differentiation Rules
PROOF Let y − log b x. Then by − x Formula 3.4.5 says that d sb x d − b x ln b dx
Differentiating this equation implicitly with respect to x , and using Formula 3.4.5, we get sb y ln bd
dy −1 dx
dy 1 1 − y − dx b ln b x ln b
and so
■
If we put b − e in Formula 1, then the factor ln b on the right side becomes ln e − 1 and we get the formula for the derivative of the natural logarithmic function log e x − ln x : d 1 sln xd − dx x
2
By comparing Formulas 1 and 2, we see one of the main reasons that natural logarithms (logarithms with base e) are used in calculus: the differentiation formula is simplest when b − e because ln e − 1.
EXAMPLE 1 Differentiate y − lnsx 3 1 1d. SOLUTION To use the Chain Rule, we let u − x 3 1 1. Then y − ln u, so dy dy du 1 du 1 3x 2 − − − 3 s3x 2 d − 3 dx du dx u dx x 11 x 11
■
In general, if we combine Formula 2 with the Chain Rule as in Example 1, we get 3
d 1 du sln ud − dx u dx
EXAMPLE 2 Find
or
d t9sxd fln tsxdg − dx tsxd
d lnssin xd. dx
SOLUTION Using (3), we have
d 1 d 1 lnssin xd − ssin xd − cos x − cot x dx sin x dx sin x
■
EXAMPLE 3 Differentiate f sxd − sln x . SOLUTION This time the logarithm is the inner function, so the Chain Rule gives
f 9sxd − 12 sln xd21y2
1 1 d 1 − sln xd − dx 2xsln x 2sln x x
■
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SECTION 3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
219
EXAMPLE 4 Differentiate f sxd − log 10 s2 1 sin xd. SOLUTION Using Formula 1 with b − 10, we have d log 10 s2 1 sin xd dx 1 d − s2 1 sin xd s2 1 sin xd ln 10 dx cos x − s2 1 sin xd ln 10
f 9sxd −
Figure 1 shows the graph of the func tion f of Example 5 together with the graph of its derivative. It gives a visual check on our calculation. Notice that f 9sxd is large negative when f is decreasing rapidly. y
EXAMPLE 5 Find
d x11 ln . dx sx 2 2
SOLUTION 1 d x11 d x11 1 ln − x 1 1 dx sx 2 2 dx sx 2 2 sx 2 2
f 1 0
■
x
−
sx 2 2 sx 2 2 ∙ 1 2 sx 1 1d( 12 )sx 2 2d21y2 x11 x22
−
x 2 2 2 12 sx 1 1d sx 1 1dsx 2 2d
−
x25 2sx 1 1dsx 2 2d
fª
SOLUTION 2 If we first expand the given function using the laws of logarithms, then the differentiation becomes easier:
FIGURE 1
d x11 d ln − flnsx 1 1d 2 12 lnsx 2 2dg dx dx sx 2 2 Figure 2 shows the graph of the func tion f sxd − ln x in Example 6 and its derivative f 9sxd − 1yx. Notice that when x is small, the graph of y − ln x is steep and so f 9sxd is large (positive or negative).
 
 
−
f sxd −
f 3
H
ln x if x . 0 lns2xd if x , 0
it follows that
f 9sxd − _3
FIGURE 2
1 x22
EXAMPLE 6 Find f 9sxd if f sxd − ln  x .
fª
_3
S D
(This answer can be left as written, but if we used a common denominator we would see that it gives the same answer as in Solution 1.) ■
SOLUTION Since
3
1 1 2 x11 2
1 if x . 0 x 1 1 s21d − if x , 0 2x x
Thus f 9sxd − 1yx for all x ± 0.
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■
220
CHAPTER 3 Differentiation Rules
The result of Example 6 is worth remembering: d 1 ln x − dx x
 
4
■ Logarithmic Differentiation The calculation of derivatives of complicated functions involving products, quotients, or powers can often be simplified by taking logarithms. The method used in the following example is called logarithmic differentiation. x 3y4 sx 2 1 1 . s3x 1 2d5 SOLUTION We take logarithms of both sides of the equation and use the Laws of Logarithms to simplify:
EXAMPLE 7 Differentiate y −
ln y − 34 ln x 1 12 lnsx 2 1 1d 2 5 lns3x 1 2d Differentiating implicitly with respect to x gives 1 dy 3 1 1 2x 3 − 1 2 25 y dx 4 x 2 x 11 3x 1 2 Solving for dyydx, we get
S
dy 3 x 15 −y 1 2 2 dx 4x x 11 3x 1 2 If we hadn’t used logarithmic differen tiation in Example 7, we would have had to use both the Quotient Rule and the Product Rule. The resulting calculation would have been horrendous.
D
Because we have an explicit expression for y, we can substitute and write dy x 3y4 sx 2 1 1 − dx s3x 1 2d5
S
D
3 x 15 1 2 2 4x x 11 3x 1 2
■
Steps in Logarithmic Differentiation 1. Take natural logarithms of both sides of an equation y − f sxd and use the Laws of Logarithms to expand the expression. 2. Differentiate implicitly with respect to x. 3. Solve the resulting equation for y9 and replace y by f sxd. If f sxd , 0 for some values of x, then ln f sxd is not defined, but we can still use logarithmic differentiation by first writing y − f sxd and then using Equation 4. We illustrate this procedure by proving the general version of the Power Rule, as promised in Section 3.1. Recall that the general version of the Power Rule states that if n is any real number and f sxd − x n, then f 9sxd − nx n21.
  
If x − 0, we can show that f 9s0d − 0 for n . 1 directly from the definition of a derivative.

PROOF OF THE POWER RULE (GENERAL VERSION) Let y − x n and use logarithmic differentiation: ln y − ln x n − n ln x x ± 0
 
 
y9 n − y x
Therefore Hence
 
y9 − n
y xn −n − nx n21 x x
■
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SECTION 3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
221
You should distinguish carefully between the Power Rule fsx n d9 − nx n21 g, where the base is variable and the exponent is constant, and the rule for differentiating exponential functions fsb x d9 − b x ln bg, where the base is constant and the exponent is variable. In general there are four cases for exponents and bases: Constant base, constant exponent
1.
d sb n d − 0 (b and n are constants) dx
Variable base, constant exponent
2.
d f f sxdg n − nf f sxdg n21 f 9sxd dx
Constant base, variable exponent
3.
d fb tsxd g − b tsxdsln bdt9sxd dx
Variable base, variable exponent
4. To find sdydxdf f sxdg tsxd, logarithmic differentiation can be used, as in the next example.
EXAMPLE 8 Differentiate y − x sx . SOLUTION 1 Since both the base and the exponent are variable, we use logarithmic differentiation: Figure 3 illustrates Example 8 by showing the graphs of f sxd − x sx and its derivative. y
S
y9 − y
1 sx
1
D S
ln x
− x sx
2 sx
2 1 ln x 2 sx
D
SOLUTION 2 Another method is to use Equation 1.5.10 to write x sx − e sx
1
FIGURE 3
y9 1 1 − sx 1 sln xd y x 2 sx
f fª
0
ln y − ln x sx − sx ln x
1
x
ln x
:
d d sx ln x d ( x sx ) − dx (e ) − e sx ln x dx (sx ln x) dx − x sx
S
2 1 ln x 2 sx
D
(as in Solution 1)
■
■ The Number e as a Limit We have shown that if f sxd − ln x, then f 9sxd − 1yx. Thus f 9s1d − 1. We now use this fact to express the number e as a limit. From the definition of a derivative as a limit, we have f 9s1d − lim
hl0
− lim
xl0
f s1 1 hd 2 f s1d f s1 1 xd 2 f s1d − lim xl0 h x lns1 1 xd 2 ln 1 1 − lim lns1 1 xd xl0 x x
− lim lns1 1 xd1yx xl0
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222
CHAPTER 3 Differentiation Rules y
Because f 9s1d − 1, we have lim lns1 1 xd1yx − 1
3 2
xl0
y=(1+x)!?®
Then, by Theorem 2.5.8 and the continuity of the exponential function, we have 1 yx
e − e1 − e limx l 0 lns11xd
1 0
x
5
1 yx
− lim e lns11xd xl0
− lim s1 1 xd1yx xl0
e − lim s1 1 xd1yx xl0
FIGURE 4 x
s1 1 xd 1yx
0.1 0.01 0.001 0.0001 0.00001 0.000001 0.0000001 0.00000001
2.59374246 2.70481383 2.71692393 2.71814593 2.71826824 2.71828047 2.71828169 2.71828181
Formula 5 is illustrated by the graph of the function y − s1 1 xd1yx in Figure 4 and a table of values for small values of x. This illustrates the fact that, correct to seven decimal places, e < 2.7182818 If we put n − 1yx in Formula 5, then n l ` as x l 01 and so an alternative expression for e is 6
e − lim
nl`
S D 11
1 n
n
■ Derivatives of Inverse Trigonometric Functions The inverse trigonometric functions were reviewed in Section 1.5. We discussed their continuity in Section 2.5 and their asymptotes in Section 2.6. Here we use implicit differentiation to find their derivatives. At the beginning of this section we observed that if f is a onetoone differentiable function, then its inverse function f 21 is also differentiable (except where its tangents are vertical). Because the trigonometric functions—with the restricted domains that we used to define their inverses—are onetoone and differentiable, it follows that the inverse trigonometric functions are also differentiable. Recall the definition of the arcsine function: y − sin21 x means sin y − x and 2 < y < 2 2 Differentiating sin y − x implicitly with respect to x, we obtain cos y
dy dy 1 − 1 or − dx dx cos y
Now cos y > 0 because 2y2 < y < y2, so cos y − s1 2 sin 2 y − s1 2 x 2 scos2 y 1 sin2 y − 1d Therefore
dy 1 1 − − dx cos y s1 2 x 2 d 1 ssin21xd − dx s1 2 x 2
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SECTION 3.6 Derivatives of Logarithmic and Inverse Trigonometric Functions
Figure 5 shows the graph of f sxd − tan21x and its derivative f 9sxd − 1ys1 1 x 2 d. Notice that f is increasing and f 9sxd is always posi tive. The fact that tan21x l 6y2 as x l 6` is reflected in the fact that f 9sxd l 0 as x l 6`.
The formula for the derivative of the arctangent function is derived in a similar way. If y − tan21x, then tan y − x. Differentiating tan y − x implicitly with respect to x, we have sec2 y
1.5 y= _6
y=tan–!x
1 1+≈
dy −1 dx dy 1 1 1 − − − 2 2 dx sec y 1 1 tan y 1 1 x2 d 1 stan21xd − dx 1 1 x2
6
_1.5
223
The inverse trigonometric functions sin21x and tan21x occur most frequently. The derivatives of the remaining four are given in the following table. The proofs of the formulas are left as exercises.
FIGURE 5
Derivatives of Inverse Trigonometric Functions The formulas for the derivatives of csc21x and sec21x depend on the defi nitions that are used for these func tions. See Exercise 82.
d 1 ssin21xd − dx s1 2 x 2
d 1 scsc21xd − 2 dx xsx 2 2 1
d 1 scos21xd − 2 dx s1 2 x 2
d 1 ssec21xd − dx xsx 2 2 1
d 1 stan21xd − dx 1 1 x2
d 1 scot21xd − 2 dx 1 1 x2
EXAMPLE 9 Differentiate (a) y −
1 and (b) f sxd − x arctansx . sin21x
SOLUTION (a) Recall that arctan x is an alternative notation for tan21x.
(b)
dy d d − ssin21xd21 − 2ssin21xd22 ssin21xd dx dx dx −2
1 ssin xd s1 2 x 2 21
f 9sxd − x −
2
1 1 1 (sx )
2
( 21 x21y2) 1 arctansx
sx 1 arctansx 2s1 1 xd
■
EXAMPLE 10 Differentiate tsxd − sec21sx 2 d. SOLUTION
t9sxd −
1 x ssx d 2 1 2
2 2
s2xd −
2 x sx 4 2 1
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■
224
CHAPTER 3 Differentiation Rules
3.6 Exercises 1. Explain why the natural logarithmic function y − ln x is used much more frequently in calculus than the other logarithmic functions y − log b x. 2–26 Differentiate the function. 2. tstd − lns3 1 t d 3. f sxd − lnsx 2 1 3x 1 5d
4. f sxd − x ln x 2 x
5. f sxd − sinsln xd
6. f sxd − lnssin xd 2
1 x
8. y −
1 ln x
9. tsxd − lnsxe 22x d
10. tstd − s1 1 ln t
11. Fstd − sln td sin t
12. pstd − ln st 2 1 1
13. y − log8sx 1 3xd
14. y − log10 sec x
15. Fssd − ln ln s
ln v 16. Psvd − 12v
2
2

5
tst 2 1 1d4
18. tstd − ln
17. T szd − 2 z log 2 z

3 2t 2 1 s
19. y − ln 3 2 2x
20. y − lnscsc x 2 cot xd
21. y − lnse2x 1 xe2x d
22. tsxd − e x
23. hsxd − e
24. y − ln
a
x bx
25. y − ln
2 ln x
Î
x 21ln x
39. y − lnsx 2 2 3x 1 1d, s3, 0d 40. y − x 2 ln x, s1, 0d
2
7. f sxd − ln
39–40 Find an equation of the tangent line to the curve at the given point.
1 1 2x 1 2 2x
26. y − log 2 sx log 5 xd
; 41. If f sxd − sin x 1 ln x, find f 9sxd. Check that your answer is reasonable by comparing the graphs of f and f 9. ind equations of the tangent lines to the curve y − sln xdyx ; 42. F at the points s1, 0d and se, 1yed. Illustrate by graphing the curve and its tangent lines. 43. Let f sxd − cx 1 lnscos xd. For what value of c is f 9sy4d − 6 ? 44. Let f sxd − log b s3x 2 2 2d. For what value of b is f 9s1d − 3? 45–56 Use logarithmic differentiation to find the derivative of the function. 45. y − sx 2 1 2d2sx 4 1 4d4 47. y −
Î
46. y −
x21 x4 1 1
e2x cos2 x x2 1 x 1 1
48. y − sx e x
2 2x
sx 1 1d2y3
49. y − x x
50. y − x 1yx
51. y − x sin x
52. y − (sx )
53. y − scos xd x
54. y − ssin xd ln x
55. y − x ln x
56. y − sln xdcos x
x
57. Find y9 if y − lnsx 2 1 y 2 d. 27. Show that
d 1 . ln( x 1 sx 2 1 1 ) − 2 1 1 dx sx
28. Show that
d ln dx
Î
1 2 cos x − csc x . 1 1 cos x

30. y −

31. y − ln sec x
x 1 2 lnsx 2 1d
60. Find
d9 sx 8 ln xd. dx 9
ln x 1 1 ln x
32. y − lns1 1 ln xd
lim
xl0
62. Show that lim
nl`
33–36 Differentiate f and find the domain of f . 33. f sxd −
59. Find a formula for f sndsxd if f sxd − lnsx 2 1d.
61. Use the definition of a derivative to prove that
29–32 Find y9 and y99. 29. y − sx ln x
58. Find y9 if x y − y x.
34. f sxd − s2 1 ln x
lns1 1 xd −1 x
S D 11
x n
n
− e x for any x . 0.
63–78 Find the derivative of the function. Simplify where possible. 63. f sxd − sin21s5xd
64. tsxd − sec21se x d
65. y − tan21sx 2 1
66. y − tan21 sx 2 d
67. y − stan21 xd 2
68. tsxd − arccos sx
37. If f sxd − lnsx 1 ln xd, find f 9s1d.
69. hsxd − sarcsin xd ln x
70. tstd − lnsarctanst 4dd
38. If f sxd − cossln x 2 d, find f 9s1d.
71. f szd − e arcsinsz d
35. f sxd − lnsx 2 2 2xd
36. f sxd − ln ln ln x
2
72. y − tan21 s x 2 s1 1 x 2 d
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
73. hstd − cot21std 1 cot21s1ytd
74. Rstd − arcsins1ytd
(b) Another way of defining sec21x that is sometimes used is to say that y − sec21x &? sec y − x and 0 < y < , y ± y2. Show that, with this definition,
75. y − x sin21 x 1 s1 2 x 2
d 1 ssec21xd − dx x sx 2 2 1
 
76. y − cos21ssin21 td
SD Î Î
77. y − tan21
x a
1 ln
83. Derivatives of Inverse Functions Suppose that f is a onetoone differentiable function and its inverse function f 21 is also differentiable. Use implicit differentiation to show that
x2a x1a
12x 11x
78. y − arctan
225
s f 21d9sxd −
1 f 9s f 21sxdd
provided that the denominator is not 0. ; 79–80 Find f 9sxd. Check that your answer is reasonable by comparing the graphs of f and f 9. 79. f sxd − s1 2 x 2 arcsin x
80. f sxd − arctansx 2 2 xd
81. Prove the formula for sdydxdscos21xd by the same method as for sdydxdssin21xd.
84–86 Use the formula in Exercise 83. 84. If f s4d − 5 and f 9s4d − 23, find s f 21d9s5d. 85. If f sxd − x 1 e x, find s f 21d9s1d. 86. If f sxd − x 3 1 3 sin x 1 2 cos x, find s f 21d9s2d.
82. (a) One way of defining sec21x is to say that y − sec21x &? sec y − x and 0 < y , y2 or < y , 3y2. Show that, with this definition,
87. Suppose that f and t are differentiable functions and let hsxd − f sxd tsxd. Use logarithmic differentiation to derive the formula h9 − t ? f t21 ? f 9 1 s ln f d ? f t ? t9
d 1 ssec21xd − dx x sx 2 2 1
88. Use the formula in Exercise 87 to find the derivative. (a) hsxd − x 3 (b) hsxd − 3 x (c) hsxd − ssin xd x
3.7 Rates of Change in the Natural and Social Sciences We know that if y − f sxd, then the derivative dyydx can be interpreted as the rate of change of y with respect to x. In this section we examine some of the applications of this idea to physics, chemistry, biology, economics, and other sciences. Let’s recall from Section 2.7 the basic idea behind rates of change. If x changes from x 1 to x 2, then the change in x is Dx − x 2 2 x 1 and the corresponding change in y is y
Dy − f sx 2 d 2 f sx 1 d Q {x™, ‡}
The difference quotient Dy f sx 2 d 2 f sx 1 d − Dx x2 2 x1
Îy
P { ⁄, fl} Îx 0
⁄
x™
mPQ average rate of change m=fª(⁄)=instantaneous rate of change
FIGURE 1
x
is the average rate of change of y with respect to x over the interval fx 1, x 2 g and can be interpreted as the slope of the secant line PQ in Figure 1. Its limit as Dx l 0 is the derivative f 9sx 1 d, which can therefore be interpreted as the instantaneous rate of change of y with respect to x or the slope of the tangent line at Psx 1, f sx 1 dd. Using Leibniz notation, we write the process in the form dy Dy − lim Dx l 0 Dx dx
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226
CHAPTER 3 Differentiation Rules
Whenever the function y − f sxd has a specific interpretation in one of the sciences, its derivative will have a specific interpretation as a rate of change. (As we discussed in Sec tion 2.7, the units for dyydx are the units for y divided by the units for x.) We now look at some of these interpretations in the natural and social sciences.
■ Physics If s − f std is the position function of a particle that is moving in a straight line, then DsyDt represents the average velocity over a time period Dt, and v − dsydt represents the instantaneous velocity (the rate of change of displacement with respect to time). The instantaneous rate of change of velocity with respect to time is acceleration: astd − v9std − s99std. This was discussed in Sections 2.7 and 2.8, but now that we know the differentiation formulas, we are able to more easily solve problems involving the motion of objects.
EXAMPLE 1 The position of a particle is given by the equation s − f std − t 3 2 6t 2 1 9t where t is measured in seconds and s in meters. (a) Find the velocity at time t. (b) What is the velocity after 2 s? After 4 s? (c) When is the particle at rest? (d) When is the particle moving forward (that is, in the positive direction)? (e) Draw a diagram to represent the motion of the particle. (f ) Find the total distance traveled by the particle during the first five seconds. (g) Find the acceleration at time t and after 4 s. (h) Graph the position, velocity, and acceleration functions for 0 < t < 5. (i) When is the particle speeding up? When is it slowing down? SOLUTION (a) The velocity function is the derivative of the position function: s − f std − t 3 2 6t 2 1 9t vstd −
ds − 3t 2 2 12t 1 9 dt
(b) The velocity after 2 s means the instantaneous velocity when t − 2, that is, v s2d −
ds dt
Z
t−2
− 3s2d2 2 12s2d 1 9 − 23 mys
The velocity after 4 s is v s4d − 3s4d2 2 12s4d 1 9 − 9 mys
(c) The particle is at rest when v std − 0, that is, 3t 2 2 12t 1 9 − 3st 2 2 4t 1 3d − 3st 2 1dst 2 3d − 0 and this is true when t − 1 or t − 3. Thus the particle is at rest after 1 s and after 3 s. (d) The particle moves in the positive direction when v std . 0, that is, 3t 2 2 12t 1 9 − 3st 2 1dst 2 3d . 0
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
t=3 s=0
t=0 s=0
s
t=1 s=4
227
This inequality is true when both factors are positive st . 3d or when both factors are negative st , 1d. Thus the particle moves in the positive direction in the time intervals t , 1 and t . 3. It moves backward (in the negative direction) when 1 , t , 3. (e) Using the information from part (d) we make a schematic sketch in Figure 2 of the motion of the particle back and forth along a line (the saxis). (f ) Because of what we learned in parts (d) and (e), we need to calculate the distances traveled during the time intervals [0, 1], [1, 3], and [3, 5] separately. The distance traveled in the first second is
 f s1d 2 f s0d  −  4 2 0  − 4 m
FIGURE 2
From t − 1 to t − 3 the distance traveled is
 f s3d 2 f s1d  −  0 2 4  − 4 m From t − 3 to t − 5 the distance traveled is
 f s5d 2 f s3d  −  20 2 0  − 20 m
25
√ 0
s
The total distance is 4 1 4 1 20 − 28 m. (g) The acceleration is the derivative of the velocity function:
a 5
astd −
d 2s dv − − 6t 2 12 dt 2 dt
as4d − 6s4d 2 12 − 12 mys 2
_12
FIGURE 3
(h) Figure 3 shows the graphs of s, v, and a. ( i) The particle speeds up when the velocity is positive and increasing (v and a are both positive) and also when the velocity is negative and decreasing (v and a are both negative). In other words, the particle speeds up when the velocity and acceleration have the same sign. (The particle is pushed in the same direction it is moving.) From Figure 3 we see that this happens when 1 , t , 2 and when t . 3. The particle slows down when v and a have opposite signs, that is, when 0 < t , 1 and when 2 , t , 3. Figure 4 summarizes the motion of the particle.
5 0 _5
s t
1
forward
FIGURE 4
a
√
slows down
backward speeds up
slows down
forward speeds up
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■
228
CHAPTER 3 Differentiation Rules
EXAMPLE 2 If a rod or piece of wire is homogeneous, then its linear density is uniform and is defined as the mass per unit length s − myld and measured in kilograms per meter. Suppose, however, that the rod is not homogeneous but that its mass measured from its left end to a point x is m − f sxd, as shown in Figure 5. x x¡
This part of the rod has mass ƒ.
FIGURE 5
x™
The mass of the part of the rod that lies between x − x 1 and x − x 2 is given by Dm − f sx 2 d 2 f sx 1 d, so the average density of that part of the rod is average density −
Dm f sx 2 d 2 f sx 1 d − Dx x2 2 x1
If we now let Dx l 0 (that is, x 2 l x 1), we are computing the average density over smaller and smaller intervals. The linear density at x 1 is the limit of these average densities as Dx l 0 ; that is, the linear density is the rate of change of mass with respect to length. Symbolically, − lim
Dx l 0
Dm dm − Dx dx
Thus the linear density of the rod is the derivative of mass with respect to length. For instance, if m − f sxd − sx , where x is measured in meters and m in kilograms, then the average density of the part of the rod given by 1 < x < 1.2 is Dm f s1.2d 2 f s1d s1.2 2 1 − − < 0.48 kgym Dx 1.2 2 1 0.2 while the density right at x − 1 is
FIGURE 6
−
dm dx
Z
x−1
−
1 2sx
Z
x−1
− 0.50 kgym
■
EXAMPLE 3 A current exists whenever electric charges move. Figure 6 shows part of a wire and electrons moving through a plane surface, shaded red. If DQ is the net charge that passes through this surface during a time period Dt, then the average current during this time interval is defined as average current −
DQ Q2 2 Q1 − Dt t2 2 t1
If we take the limit of this average current over smaller and smaller time intervals, we get what is called the current I at a given time t1: I − lim
Dt l 0
DQ dQ − Dt dt
Thus the current is the rate at which charge flows through a surface. It is measured in units of charge per unit time (often coulombs per second, called amperes). ■
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
229
Velocity, density, and current are not the only rates of change that are important in physics. Others include power (the rate at which work is done), the rate of heat flow, temperature gradient (the rate of change of temperature with respect to position), and the rate of decay of a radioactive substance in nuclear physics.
■ Chemistry EXAMPLE 4 A chemical reaction results in the formation of one or more substances (called products) from one or more starting materials (called reactants). For instance, the “equation” 2H2 1 O2 l 2H2 O indicates that two molecules of hydrogen and one molecule of oxygen form two molecules of water. Let’s consider the reaction A1BlC where A and B are the reactants and C is the product. The concentration of a reactant A is the number of moles (1 mole − 6.022 3 10 23 molecules) per liter and is denoted by fAg. The concentration varies during a reaction, so fAg, fBg, and fCg are all functions of time std. The average rate of reaction of the product C over a time interval t1 < t < t2 is DfCg fCgst2 d 2 fCgst1 d − Dt t2 2 t1 But chemists are interested in the instantaneous rate of reaction because it gives information about the mechanism of the chemical reaction. The instantaneous rate of reaction is obtained by taking the limit of the average rate of reaction as the time interval Dt approaches 0 : rate of reaction − lim
Dt l 0
DfCg dfCg − Dt dt
Since the concentration of the product increases as the reaction proceeds, the derivative dfCg ydt will be positive, and so the rate of reaction of C is positive. The concentrations of the reactants, however, decrease during the reaction, so, to make the rates of reaction of A and B positive numbers, we put minus signs in front of the derivatives dfAg ydt and dfBg ydt. Since fAg and fBg each decrease at the same rate that fCg increases, we have rate of reaction −
dfCg dfAg dfBg −2 −2 dt dt dt
More generally, it turns out that for a reaction of the form aA 1 bB l cC 1 dD we have 2
1 dfAg 1 dfBg 1 dfCg 1 dfDg −2 − − a dt b dt c dt d dt
The rate of reaction can be determined from data and graphical methods. In some cases there are explicit formulas for the concentrations as functions of time that enable us to compute the rate of reaction (see Exercise 26). ■
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CHAPTER 3 Differentiation Rules
EXAMPLE 5 One of the quantities of interest in thermodynamics is compressibility. If a given substance is kept at a constant temperature, then its volume V depends on its pressure P. We can consider the rate of change of volume with respect to pressure— namely, the derivative dVydP. As P increases, V decreases, so dVydP , 0. The compressibility is defined by introducing a minus sign and dividing this derivative by the volume V: isothermal compressibility − − 2
1 dV V dP
Thus measures how fast, per unit volume, the volume of a substance decreases as the pressure on it increases at constant temperature. For instance, the volume V (in cubic meters) of a sample of air at 258C was found to be related to the pressure P (in kilopascals) by the equation V−
5.3 P
The rate of change of V with respect to P when P − 50 kPa is dV dP
Z
P−50
Z
−2
5.3 P2
−2
5.3 − 20.00212 m 3ykPa 2500
P−50
The compressibility at that pressure is
−2
1 dV V dP
Z
P−50
−
0.00212 − 0.02 sm 3ykPadym 3 5.3 50
■
■ Biology EXAMPLE 6 Let n − f std be the number of individuals in an animal or plant popula tion at time t. The change in the population size between the times t − t1 and t − t2 is Dn − f st2 d 2 f st1 d, and so the average rate of growth during the time period t1 < t < t2 is average rate of growth −
Dn f st2 d 2 f st1 d − Dt t2 2 t1
The instantaneous rate of growth is obtained from this average rate of growth by letting the time period Dt approach 0: growth rate − lim
Dt l 0
Dn dn − Dt dt
Strictly speaking, this is not quite accurate because the actual graph of a population function n − f std would be a step function that is discontinuous whenever a birth or death occurs and therefore not differentiable. However, for a large animal
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
231
or plant population, we can replace the graph by a smooth approximating curve as in Figure 7. n
FIGURE 7 A smooth curve approximating a growth function
t
0
To be more specific, consider a population of bacteria in a homogeneous nutrient medium. Suppose that by sampling the population at certain intervals it is determined that the population doubles every hour. If the initial population is n0 and the time t is measured in hours, then f s1d − 2f s0d − 2n0 f s2d − 2f s1d − 2 2n0 Science Photo Library / Alamy Stock Photo
f s3d − 2f s2d − 2 3n0 and, in general, f std − 2 t n0 The population function is n − n0 2 t. In Section 3.4 we showed that E. coli bacteria measure about 2 micrometers (mm) long and 0.75 mm wide. The image was produced with a scanning electron microscope.
d sb x d − b x ln b dx So the rate of growth of the bacteria population at time t is dn d − sn0 2t d − n0 2t ln 2 dt dt For example, suppose that we start with an initial population of n0 − 100 bacteria. Then the rate of growth after 4 hours is dn dt
Z
t−4
− 100 24 ln 2 − 1600 ln 2 < 1109
This means that, after 4 hours, the bacteria population is growing at a rate of about 1109 bacteria per hour.
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■
232
CHAPTER 3 Differentiation Rules
EXAMPLE 7 When we consider the flow of blood through a blood vessel, such as a vein or artery, we can model the shape of the blood vessel by a cylindrical tube with radius R and length l as illustrated in Figure 8. R
r
FIGURE 8 Blood flow in an artery
l
Because of friction at the walls of the tube, the velocity v of the blood is greatest along the central axis of the tube and decreases as the distance r from the axis increases until v becomes 0 at the wall. The relationship between v and r is given by the law of laminar flow, which was experimentally derived by the French physicist Jean Léonard Marie Poiseuille in 1838. This law states that 1 For more detailed information, see W. Nichols, M. O’Rourke, and C. Vlachopoulos (eds.), McDonald’s Blood Flow in Arteries: Theoretical, Experimental, and Clinical Principles, 6th ed. (Boca Raton, FL, 2011).
v−
P sR 2 2 r 2 d 4l
where is the viscosity of the blood and P is the pressure difference between the ends of the tube. If P and l are constant, then v is a function of r with domain f0, Rg. The average rate of change of the velocity as we move from r − r1 outward to r − r2 is given by Dv vsr2 d 2 vsr1 d − Dr r2 2 r1 and if we let Dr l 0, we obtain the velocity gradient, that is, the instantaneous rate of change of velocity with respect to r : velocity gradient − lim
Dr l 0
Dv dv − Dr dr
Using Equation 1, we obtain dv P Pr − s0 2 2rd − 2 dr 4l 2l For one of the smaller human arteries we can take − 0.027, R − 0.008 cm, l − 2 cm, and P − 4000 dynesycm2, which gives v−
4000 s0.000064 2 r 2 d 4s0.027d2
< 1.85 3 10 4s6.4 3 10 25 2 r 2 d At r − 0.002 cm the blood is flowing at a speed of vs0.002d < 1.85 3 10 4s64 3 1026 2 4 3 10 26 d − 1.11 cmys
and the velocity gradient at that point is dv dr
Z
r−0.002
−2
4000s0.002d < 274 scmysdycm 2s0.027d2
To get a feeling for what this statement means, let’s change our units from centimeters
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
233
to micrometers (1 cm − 10,000 mm). Then the radius of the artery is 80 mm. The velocity at the central axis is 11,850 mmys, which decreases to 11,110 mmys at a distance of r − 20 mm. The fact that dvydr − 274 (mmys)ymm means that, when r − 20 mm, the velocity is decreasing at a rate of about 74 mmys for each micrometer that we proceed away from the center. ■
■ Economics EXAMPLE 8 Suppose Csxd is the total cost that a company incurs in producing
x units of a certain commodity. The function C is called a cost function. If the number of items produced is increased from x 1 to x 2, then the additional cost is DC − Csx 2 d 2 Csx 1 d, and the average rate of change of the cost is DC Csx 2 d 2 Csx 1 d Csx 1 1 Dxd 2 Csx 1 d − − Dx x2 2 x1 Dx
The limit of this quantity as Dx l 0, that is, the instantaneous rate of change of cost with respect to the number of items produced, is called the marginal cost by economists: marginal cost − lim
Dx l 0
DC dC − Dx dx
[Since x often takes on only integer values, it may not make literal sense to let Dx approach 0, but we can always replace Csxd by a smooth approximating function as in Example 6.] Taking Dx − 1 and n large (so that Dx is small compared to n), we have C9snd < Csn 1 1d 2 Csnd Thus the marginal cost of producing n units is approximately equal to the cost of producing one more unit [the sn 1 1dst unit]. It is often appropriate to represent a total cost function by a polynomial Csxd − a 1 bx 1 cx 2 1 dx 3 where a represents the overhead cost (rent, heat, maintenance) and the other terms represent the cost of raw materials, labor, and so on. (The cost of raw materials may be proportional to x, but labor costs might depend partly on higher powers of x because of overtime costs and inefficiencies involved in largescale operations.) For instance, suppose a company has estimated that the cost (in dollars) of pro ducing x items is Csxd − 10,000 1 5x 1 0.01x 2 Then the marginal cost function is C9sxd − 5 1 0.02x The marginal cost at the production level of 500 items is C9s500d − 5 1 0.02s500d − $15yitem
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CHAPTER 3 Differentiation Rules
This gives the rate at which costs are increasing with respect to the production level when x − 500 and predicts the cost of the 501st item. The actual cost of producing the 501st item is Cs501d 2 Cs500d − f10,000 1 5s501d 1 0.01s501d2 g − 2 f10,000 1 5s500d 1 0.01s500d2 g − $15.01 Notice that C9s500d < Cs501d 2 Cs500d.
■
Economists also study marginal demand, marginal revenue, and marginal profit, the derivatives of the demand, revenue, and profit functions. These will be considered in Chapter 4 after we have developed techniques for finding the maximum and minimum values of functions.
■ Other Sciences Rates of change occur in all the sciences. A geologist is interested in knowing the rate at which an intruded body of molten rock cools by conduction of heat into surrounding rocks. An engineer wants to know the rate at which water flows out of a reservoir. An urban geographer is interested in the rate of change of the population density in a city as the distance from the city center increases. A meteorologist is concerned with the rate of change of atmospheric pressure with respect to height (see Exercise 3.8.19). In psychology, those interested in learning theory study the learning curve, which graphs the performance Pstd of someone learning a skill as a function of the training time t. Of particular interest is the rate at which performance improves as time passes, that is, dPydt. Psychologists have also studied the phenomenon of memory and have developed models for the rate of memory retention (see Exercise 42). They also study the difficulty involved in performing certain tasks and the rate at which difficulty increases when a given parameter is changed (see Exercise 43). In sociology, differential calculus is used in analyzing the spread of rumors (or innovations or fads or fashions). If pstd denotes the proportion of a population that knows a rumor by time t, then the derivative dpydt represents the rate of spread of the rumor (see Exercise 3.4.90).
■ A Single Idea, Many Interpretations Velocity, density, current, power, and temperature gradient in physics; rate of reaction and compressibility in chemistry; rate of growth and blood velocity gradient in biology; marginal cost and marginal profit in economics; rate of heat flow in geology; rate of improvement of performance in psychology; rate of spread of a rumor in sociology— these are all special cases of a single mathematical concept, the derivative. All of these different applications of the derivative illustrate the fact that part of the power of mathematics lies in its abstractness. A single abstract mathematical concept (such as the derivative) can have different interpretations in each of the sciences. When we develop the properties of the mathematical concept once and for all, we can then turn around and apply these results to all of the sciences. This is much more efficient than developing properties of special concepts in each separate science. The French mathematician Joseph Fourier (1768–1830) put it succinctly: “Mathematics compares the most diverse phenomena and discovers the secret analogies that unite them.”
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
235
3.7 Exercises 1–4 A particle moves according to a law of motion s − f std, t > 0, where t is measured in seconds and s in meters. (a) Find the velocity at time t. (b) What is the velocity after 1 second? (c) When is the particle at rest? (d) When is the particle moving in the positive direction? (e) Find the total distance traveled during the first 6 seconds. (f ) Draw a diagram like Figure 2 to illustrate the motion of the particle. (g) Find the acceleration at time t and after 1 second. ; (h) Graph the position, velocity, and acceleration functions for 0 < t < 6. (i) When is the particle speeding up? When is it slowing down? 9t t2 1 9
1. f std − t 3 2 8t 2 1 24t
2. f std −
3. f std − sinsty2d
4. f std − t 2e 2t
5. Graphs of the velocity functions of two particles are shown, where t is measured in seconds. When is each particle speeding up? When is it slowing down? Explain. (b) √ √
(a) √√
00
11
tt
00
11
tt
6. Graphs of the position functions of two particles are shown, where t is measured in seconds. When is the velocity of each particle positive? When is it negative? When is each particle speeding up? When is it slowing down? Explain. (a) s s
00 1 1
00 1 1
1 0
1
x
8. For the particle described in Exercise 7, sketch a graph of the acceleration function. When is the particle speeding up? When is it slowing down? When is it traveling at a constant speed? 9. The height (in meters) of a projectile shot vertically upward from a point 2 m above ground level with an initial velocity of 24.5 mys is h − 2 1 24.5t 2 4.9t 2 after t seconds. (a) Find the velocity after 2 s and after 4 s. (b) When does the projectile reach its maximum height? (c) What is the maximum height? (d) When does it hit the ground? (e) With what velocity does it hit the ground? 10. I f a ball is thrown vertically upward with a velocity of 24.5 mys, then its height after t seconds is s − 24.5t 2 4.9t 2. (a) What is the maximum height reached by the ball? (b) What is the velocity of the ball when it is 29.4 above the ground on its way up? On its way down? 11. I f a rock is thrown vertically upward from the surface of Mars with velocity 15 mys, its height after t seconds is h − 15t 2 1.86t 2. (a) What is the velocity of the rock after 2 s? (b) What is the velocity of the rock when its height is 25 m on its way up? On its way down? 12. A particle moves with position function s − t 4 2 4t 3 2 20t 2 1 20t t > 0
(b) s s
t t
y
t t
7. Suppose that the graph of the velocity function of a particle is as shown in the figure, where t is measured in seconds. When is the particle traveling forward (in the positive direction)? When is it traveling backward? What is happening when 5 , t , 7 ?
(a) At what time does the particle have a velocity of 20 mys? (b) At what time is the acceleration 0? What is the significance of this value of t ?
13. (a) A company makes computer chips from square wafers of silicon. A process engineer wants to keep the side length of a wafer very close to 15 mm and needs to know how the area Asxd of a wafer changes when the side length x changes. Find A9s15d and explain its meaning in this situation. (b) Show that the rate of change of the area of a square with respect to its side length is half its perimeter. Try to explain geometrically why this is true by drawing a square whose side length x is increased by an amount Dx. How can you approximate the resulting change in area DA if Dx is small?
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CHAPTER 3 Differentiation Rules
14. (a) Sodium chlorate crystals are easy to grow in the shape of cubes by allowing a solution of water and sodium chlorate to evaporate slowly. If V is the volume of such a cube with side length x, calculate dVydx when x − 3 mm and explain its meaning. (b) Show that the rate of change of the volume of a cube with respect to its edge length is equal to half the surface area of the cube. Explain geometrically why this result is true by arguing by analogy with Exercise 13(b). 15. (a) Find the average rate of change of the area of a circle with respect to its radius r as r changes from (i) 2 to 3 (ii) 2 to 2.5 (iii) 2 to 2.1 (b) Find the instantaneous rate of change when r − 2. (c) Show that the rate of change of the area of a circle with respect to its radius (at any r) is equal to the circumference of the circle. Try to explain geometrically why this is true by drawing a circle whose radius is increased by an amount Dr. How can you approximate the resulting change in area DA if Dr is small? 16. A stone is dropped into a lake, creating a circular ripple that travels outward at a speed of 60 cmys. Find the rate at which the area within the circle is increasing after (a) 1 s, (b) 3 s, and (c) 5 s. What can you conclude? 17. A spherical balloon is being inflated. Find the rate of increase of the surface area sS − 4r 2 d with respect to the radius r when r is (a) 20 cm, (b) 40 cm, and (c) 60 cm. What conclusion can you make? 18. (a) The volume of a growing spherical cell is V − 43 r 3, where the radius r is measured in micrometers (1 μm − 1026 m). Find the average rate of change of V with respect to r when r changes from (i) 5 to 8 μm (ii) 5 to 6 μm (iii) 5 to 5.1 μm (b) Find the instantaneous rate of change of V with respect to r when r − 5 μm. (c) Show that the rate of change of the volume of a sphere with respect to its radius is equal to its surface area. Explain geometrically why this result is true. Argue by analogy with Exercise 15(c). 19. T he mass of the part of a metal rod that lies between its left end and a point x meters to the right is 3x 2 kg. Find the linear density (see Example 2) when x is (a) 1 m, (b) 2 m, and (c) 3 m. Where is the density the highest? The lowest? 20. I f a cylindrical water tank holds 5000 liters, and the water drains from the bottom of the tank in 40 minutes, then Torricelli’s Law gives the volume V of water remaining in the tank after t minutes as 1 V − 5000 (1 2 40 t) 0 < t < 40 2
Find the rate at which water is draining from the tank after (a) 5 min, (b) 10 min, (c) 20 min, and (d) 40 min. At what time is the water flowing out the fastest? The slowest? Summarize your findings.
21. T he quantity of charge Q in coulombs (C) that has passed through a point in a wire up to time t (measured in seconds) is given by Qstd − t 3 2 2t 2 1 6t 1 2. Find the current when (a) t − 0.5 s and (b) t − 1 s. (See Example 3. The unit of current is an ampere [1 A − 1 Cys].) At what time is the current lowest? 22. N ewton’s Law of Gravitation says that the magnitude F of the force exerted by a body of mass m on a body of mass M is F−
GmM r2
w here G is the gravitational constant and r is the distance between the bodies. (a) Find dFydr and explain its meaning. What does the minus sign indicate? (b) Suppose it is known that the earth attracts an object with a force that decreases at the rate of 2 Nykm when r − 20,000 km. How fast does this force change when r − 10,000 km? 23. The force F acting on a body with mass m and velocity v is the rate of change of momentum: F − sdydtd smvd. If m is constant, this becomes F − ma, where a − dvydt is the acceleration. But in the theory of relativity, the mass of a particle varies with v as follows: m − m 0 ys1 2 v 2yc 2 where m 0 is the mass of the particle at rest and c is the speed of light. Show that m0a F− s1 2 v 2yc 2 d3y2 24. S ome of the highest tides in the world occur in the Bay of Fundy on the Atlantic Coast of Canada. At Hopewell Cape the water depth at low tide is about 2.0 m and at high tide it is about 12.0 m. The natural period of oscillation is a little more than 12 hours and on a day in June, high tide occurred at 6:45 am. This helps explain the following model for the water depth D (in meters) as a function of the time t (in hours after midnight) on that day: Dstd − 7 1 5 cosf0.503st 2 6.75dg How fast was the tide rising (or falling) at the following times? (a) 3:00 am (b) 6:00 am (c) 9:00 am (d) Noon 25. B oyle’s Law states that when a sample of gas is compressed at a constant temperature, the product of the pressure and the volume remains constant: PV − C. (a) Find the rate of change of volume with respect to pressure. (b) A sample of gas is in a container at low pressure and is steadily compressed at constant temperature for 10 minutes. Is the volume decreasing more rapidly at the beginning or the end of the 10 minutes? Explain. (c) Prove that the isothermal compressibility (see Example 5) is given by − 1yP.
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SECTION 3.7 Rates of Change in the Natural and Social Sciences
26. I f, in Example 4, one molecule of the product C is formed from one molecule of the reactant A and one molecule of the reactant B, and the initial concentrations of A and B have a common value fAg − fBg − a molesyL, then fCg − a 2ktysakt 1 1d where k is a constant. (a) Find the rate of reaction at time t. (b) Show that if x − fCg, then dx − ksa 2 xd 2 dt
(c) What happens to the concentration as t l `? (d) What happens to the rate of reaction as t l `? (e) What do the results of parts (c) and (d) mean in practical terms?
where t is measured in hours. At time t − 0 the population is 20 cells and is increasing at a rate of 12 cellsyhour. Find the values of a and b. According to this model, what happens to the yeast population in the long run? 29. T he table gives the world population Pstd, in millions, where t is measured in years and t − 0 corresponds to the year 1900.
t
Population (millions)
t
Population (millions)
0 10 20 30 40 50
1650 1750 1860 2070 2300 2560
60 70 80 90 100 110
3040 3710 4450 5280 6080 6870
(a) Estimate the rate of population growth in 1920 and in 1980 by averaging the slopes of two secant lines. (b) Use a graphing calculator or computer to find a cubic function (a thirddegree polynomial) that models the data. (c) Use your model in part (b) to find a model for the rate of population growth. (d) Use part (c) to estimate the rates of growth in 1920 and 1980. Compare with your estimates in part (a).
(e) In Section 1.1 we modeled Pstd with the exponential function f std − s1.43653 3 10 9 d s1.01395d t
Use this model to find a model for the rate of population growth. (f ) Use your model in part (e) to estimate the rate of growth in 1920 and 1980. Compare with your estimates in parts (a) and (d). (g) Estimate the rate of growth in 1985. 30. T he table shows how the average age of first marriage of Japanese women has varied since 1950.
27. I n Example 6 we considered a bacteria population that doubles every hour. Suppose that another population of bacteria triples every hour and starts with 400 bacteria. Find an expression for the number n of bacteria after t hours and use it to estimate the rate of growth of the bacteria population after 2.5 hours. 28. T he number of yeast cells in a laboratory culture increases rapidly initially but levels off eventually. The population is modeled by the function a n − f std − 1 1 be20.7t
237
t
Astd
t
Astd
1950 1955 1960 1965 1970 1975 1980
23.0 23.8 24.4 24.5 24.2 24.7 25.2
1985 1990 1995 2000 2005 2010 2015
25.5 25.9 26.3 27.0 28.0 28.8 29.4
(a) Use a graphing calculator or computer to model these data with a fourthdegree polynomial. (b) Use part (a) to find a model for A9std. (c) Estimate the rate of change of marriage age for women in 1990. (d) Graph the data points and the models for A and A9.
31. R efer to the law of laminar flow given in Example 7. Consider a blood vessel with radius 0.01 cm, length 3 cm, pressure difference 3000 dynesycm2, and viscosity − 0.027. (a) Find the velocity of the blood along the centerline r − 0, at radius r − 0.005 cm, and at the wall r − R − 0.01 cm. (b) Find the velocity gradient at r − 0, r − 0.005, and r − 0.01. (c) Where is the velocity the greatest? Where is the velocity changing most? 32. T he frequency of vibrations of a vibrating violin string is given by 1 T f− 2L
Î
where L is the length of the string, T is its tension, and is its linear density. [See Chapter 11 in D. E. Hall, Musical Acoustics, 3rd ed. (Pacific Grove, CA, 2002).] (a) Find the rate of change of the frequency with respect to (i) the length (when T and are constant), (ii) the tension (when L and are constant), and (iii) the linear density (when L and T are constant). (b) The pitch of a note (how high or low the note sounds) is determined by the frequency f . (The higher the frequency, the higher the pitch.) Use the signs of the
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238
CHAPTER 3 Differentiation Rules
derivatives in part (a) to determine what happens to the pitch of a note (i) when the effective length of a string is decreased by placing a finger on the string so a shorter portion of the string vibrates, (ii) when the tension is increased by turning a tuning peg, (iii) when the linear density is increased by switching to another string.
33. S uppose that the cost (in dollars) for a company to produce x pairs of a new line of jeans is Csxd − 2000 1 3x 1 0.01x 2 1 0.0002x 3
(a) Find the marginal cost function. (b) Find C9s100d and explain its meaning. What does it predict? (c) Compare C9s100d with the cost of manufacturing the 101st pair of jeans.
34. The cost function for a certain commodity is Csqd − 84 1 0.16q 2 0.0006q 2 1 0.000003q 3
(a) Find and interpret C9s100d. (b) Compare C9s100d with the cost of producing the 101st item.
35. If psxd is the total value of the production when there are x workers in a plant, then the average productivity of the workforce at the plant is Asxd −
filters out urea. Under certain conditions, the duration of dialysis required, given that the initial urea concentration is c . 1, is given by the equation
S
t − ln
38. I nvasive species often display a wave of advance as they colonize new areas. Mathematical models based on random dispersal and reproduction have demonstrated that the speed with which such waves move is given by the function f srd − 2 sDr , where r is the reproductive rate of individuals and D is a parameter quantifying dispersal. Calculate the derivative of the wave speed with respect to the reproductive rate r and explain its meaning. 39. T he gas law for an ideal gas at absolute temperature T (in kelvins), pressure P (in atmospheres), and volume V (in liters) is PV − nRT, where n is the number of moles of the gas and R − 0.0821 is the gas constant. Suppose that, at a certain instant, P − 8.0 atm and is increasing at a rate of 0.10 atmymin and V − 10 L and is decreasing at a rate of 0.15 Lymin. Find the rate of change of T with respect to time at that instant if n − 10 mol. 40. I n a fish farm, a population of fish is introduced into a pond and harvested regularly. A model for the rate of change of the fish population is given by the equation
S
40 1 24x 0.4 1 1 4x 0.4
has been used to model the dependence of R on x when R is measured in square millimeters and x is measured in appropriate units of brightness. (a) Find the sensitivity. (b) Illustrate part (a) by graphing both R and S as functions ; of x. Comment on the values of R and S at low levels of brightness. Is this what you would expect? 37. Patients undergo dialysis treatment to remove urea from their blood when their kidneys are not functioning properly. Blood is diverted from the patient through a machine that
D
Pstd dP Pstd 2 Pstd − r0 1 2 dt Pc where r0 is the birth rate of the fish, Pc is the maximum population that the pond can sustain (called the carrying capacity), and is the percentage of the population that is harvested. (a) What value of dPydt corresponds to a stable population? (b) If the pond can sustain 10,000 fish, the birth rate is 5%, and the harvesting rate is 4%, find the stable population level. (c) What happens if is raised to 5%?
(a) Find A9sxd. Why does the company want to hire more workers if A9sxd . 0 ? (b) Show that A9sxd . 0 if p9sxd is greater than the average productivity.
R−
D
Calculate the derivative of t with respect to c and interpret it.
psxd x
36. I f R denotes the reaction of the body to some stimulus of strength x, the sensitivity S is defined to be the rate of change of the reaction with respect to x. A particular example is that when the brightness x of a light source is increased, the eye reacts by decreasing the area R of the pupil. The experimental formula
3c 1 s9c 2 2 8c 2
41. I n the study of ecosystems, predatorprey models are often used to study the interaction between species. Consider populations of tundra wolves, given by Wstd, and caribou, given by Cstd, in northern Canada. The interaction has been modeled by the equations dC dW − aC 2 bCW − 2cW 1 dCW dt dt
(a) What values of dCydt and dWydt correspond to stable populations? (b) How would the statement “The caribou go extinct” be represented mathematically? (c) Suppose that a − 0.05, b − 0.001, c − 0.05, and d − 0.0001. Find all population pairs sC, W d that lead to stable populations. According to this model, is it possible for the two species to live in balance or will one or both species become extinct?
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SECTION 3.8 Exponential Growth and Decay
between the distance D to the target and width W of the target. According to Fitts’ law, the index I of difficulty is modeled by
42. Hermann Ebbinghaus (1850 –1909) pioneered the study of memory. A 2011 article in the Journal of Mathematical Psychology presents the mathematical model
S D
Rstd − a 1 bs1 1 ctd2
for the Ebbinghaus forgetting curve, where Rstd is the fraction of memory retained t days after learning a task; a, b, and c are experimentally determined constants between 0 and 1; is a positive constant; and Rs0d − 1. The constants depend on the type of task being learned. (a) What is the rate of change of retention t days after a task is learned? (b) Do you forget how to perform a task faster soon after learning it or a long time after you have learned it? (c) What fraction of memory is permanent?
43. The difficulty of “acquiring a target” (such as using a mouse to click on an icon on a computer screen) depends on the ratio
239
I − log 2
2D W
This law is used for designing products that involve human– computer interactions. (a) If W is held constant, what is the rate of change of I with respect to D? Does this rate increase or decrease with increasing values of D? (b) If D is held constant, what is the rate of change of I with respect to W? What does the negative sign in your answer indicate? Does this rate increase or decrease with increasing values of W? (c) Do your answers to parts (a) and (b) agree with your intuition?
3.8 Exponential Growth and Decay In many natural phenomena, quantities grow or decay at a rate proportional to their size. For instance, if y − f std is the number of individuals in a population of animals or bacteria at time t, then it seems reasonable to expect that the rate of growth f 9std is proportional to the population f std; that is, f 9std − kf std for some constant k. Indeed, under ideal conditions (unlimited environment, adequate nutrition, immunity to disease) the mathematical model given by the equation f 9std − kf std predicts what actually happens fairly accurately. Another example occurs in nuclear physics: the mass of a radioactive substance decays at a rate proportional to the mass. In chemistry, the rate of a uni molecular firstorder reaction is proportional to the concentration of the substance. In finance, the value of a savings account with continuously compounded interest increases at a rate proportional to that value. In general, if ystd is the value of a quantity y at time t and if the rate of change of y with respect to t is proportional to its size ystd at any time, then 1
dy − ky dt
where k is a constant. Equation 1 is sometimes called the law of natural growth (if k . 0d or the law of natural decay (if k , 0). It is called a differential equation because it involves an unknown function y and its derivative dyydt. It’s not hard to think of a solution of Equation 1. This equation asks us to find a function whose derivative is a constant multiple of itself. We have met such functions in this chapter. Any exponential function of the form ystd − Ce kt, where C is a constant, satisfies dy − Cske kt d − ksCe kt d − ky dt We will see in Section 9.4 that any function that satisfies dyydt − ky must be of the form y − Ce kt. To see the significance of the constant C, we observe that ys0d − Ce k0 − C
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CHAPTER 3 Differentiation Rules
Therefore C is the initial value of the function. 2 Theorem The only solutions of the differential equation dyydt − ky are the exponential functions ystd − ys0de kt
■ Population Growth What is the significance of the proportionality constant k ? In the context of population growth, where Pstd is the size of a population at time t, we can write 3
dPydt dP −k − kP or P dt
The quantity dPydt P is the growth rate divided by the population size; it is called the relative growth rate. According to (3), instead of saying “the growth rate is proportional to population size” we could say “the relative growth rate is constant.” Then Theorem 2 says that a population with constant relative growth rate must grow exponentially. Notice that the relative growth rate k appears as the coefficient of t in the exponential function Ce kt. For instance, if dP − 0.02P dt and t is measured in years, then the relative growth rate is k − 0.02 and the population grows at a relative rate of 2% per year. If the population at time 0 is P0 , then the expression for the population is Pstd − P0 e 0.02t
EXAMPLE 1 Use the fact that the world population was 2560 million in 1950 and 3040 million in 1960 to model the population of the world in the second half of the 20th century. (Assume that the growth rate is proportional to the population size.) What is the relative growth rate? Use the model to estimate the world population in 1993 and to predict the population in the year 2025. SOLUTION We measure the time t in years and let t − 0 in the year 1950. We measure the population Pstd in millions of people. Then Ps0d − 2560 and Ps10d − 3040. Since we are assuming that dPydt − kP, Theorem 2 gives Pstd − Ps0de kt − 2560e kt Ps10d − 2560e 10k − 3040 k−
1 3040 ln < 0.017185 10 2560
The relative growth rate is about 1.7% per year and the model is Pstd − 2560e 0.017185t
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SECTION 3.8 Exponential Growth and Decay
241
We estimate that the world population in 1993 was Ps43d − 2560e 0.017185s43d < 5360 million The model predicts that the population in 2025 will be Ps75d − 2560e 0.017185s75d < 9289 million The graph in Figure 1 shows that the model is fairly accurate to the end of the 20th century (the dots represent the actual population), so the estimate for 1993 is quite reliable. But the prediction for 2025 may not be so accurate. P 6000
P=2560e 0.017185t
Population (in millions)
FIGURE 1 A model for world population growth in the second half of the 20th century
0
20
Years since 1950
40
t
■
■ Radioactive Decay Radioactive substances decay by spontaneously emitting radiation. If mstd is the mass remaining from an initial mass m0 of the substance after time t, then the relative decay rate 2
dmydt m
has been found experimentally to be constant. (Since dmydt is negative, the relative decay rate is positive.) It follows that dm − km dt where k is a negative constant. In other words, radioactive substances decay at a rate proportional to the remaining mass. This means that we can use Theorem 2 to show that the mass decays exponentially: mstd − m0 e kt Physicists express the rate of decay in terms of halflife, the time required for half of any given quantity to decay.
EXAMPLE 2 The halflife of radium226 is 1590 years. (a) A sample of radium226 has mass 100 mg. Find a formula for the mass of the sample that remains after t years. (b) Find the mass remaining after 1000 years correct to the nearest milligram. (c) When will the mass be reduced to 30 mg? SOLUTION (a) Let mstd be the mass of radium226 (in milligrams) that remains after t years. Then dmydt − km and ms0d − 100, so Theorem 2 gives mstd − ms0de kt − 100e kt
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CHAPTER 3 Differentiation Rules
In order to determine the value of k, we use the fact that ms1590d − 12 s100d. Thus 100e 1590k − 50 so e 1590k − 12 1590k − ln 12 − 2ln 2
and
k−2
ln 2 1590
mstd − 100e2sln 2dty1590
Therefore
We could use the fact that e ln 2 − 2 to write the expression for mstd in the alternative form mstd − 100 3 2 2ty1590 (b) The mass remaining after 1000 years is ms1000d − 100e2sln 2d1000y1590 < 65 mg (c) We want to find the value of t such that mstd − 30, that is, 100e2sln 2dty1590 − 30 or e2sln 2dty1590 − 0.3 We solve this equation for t by taking the natural logarithm of both sides: 150
2 m=100e_(ln 2)t/1590
Thus
ln 2 t − ln 0.3 1590 t − 21590
m=30 4000
0
FIGURE 2
ln 0.3 < 2762 years ln 2
■
As a check on our work in Example 2, we use a calculator or computer to draw the graph of mstd in Figure 2 together with the horizontal line m − 30. These curves intersect when t < 2800, and this agrees with the answer to part (c).
■ Newton’s Law of Cooling Newton’s Law of Cooling states that the rate of cooling of an object is proportional to the temperature difference between the object and its surroundings, provided that this difference is not too large. (This law also applies to warming.) If we let Tstd be the temperature of the object at time t and Ts be the temperature of the surroundings, then we can formulate Newton’s Law of Cooling as a differential equation: dT − ksT 2 Ts d dt where k is a constant. This equation is not quite the same as Equation 1, so we make the change of variable ystd − Tstd 2 Ts . Because Ts is constant, we have y9std − T 9std and so the equation becomes dy − ky dt We can then use Theorem 2 to find an expression for y, from which we can find T.
EXAMPLE 3 A bottle of iced tea at room temperature (24°C) is placed in a refrigerator where the temperature is 7°C. After half an hour the tea has cooled to 16°C. (a) What is the temperature of the tea after another half hour? (b) How long does it take for the tea to cool to 10°C ?
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SECTION 3.8 Exponential Growth and Decay
243
SOLUTION (a) Let Tstd be the temperature of the tea after t minutes. The surrounding temperature is Ts − 78C, so Newton’s Law of Cooling states that dT − ksT 2 7d dt If we let y − T 2 7, then ys0d − Ts0d 2 7 − 24 2 7 − 17, so y satisfies dy − ky ys0d − 17 dt ystd − ys0de kt − 17e kt
and by (2) we have
We are given that Ts30d − 16, so ys30d − 16 2 7 − 9 and 9 17e 30k − 9 e 30k − 17
Taking logarithms, we have k−
9 ln (17 ) < 20.02120 30
Thus ystd − 17e 20.02120t Tstd − 7 1 17e 20.02120t Ts60d − 7 1 17e 20.02120s60d < 11.8 So after another half hour the tea has cooled to about 11.8°C. (b) We have Tstd − 10 when 7 1 17e 20.02120t 5 10 3 e 20.02120t 5 17
T (°F) 24
t5
3 ) ln (17 < 81.8 20.02120
The tea cools to 10°C after about 1 hour 22 minutes.
7
■
Notice that in Example 3 we have 0
FIGURE 3
30
60
90
t (min)
lim Tstd − lim s7 1 17e 20.02120t d − 7 1 17 0 − 7
tl`
tl`
This means that, as expected, the temperature of the tea approaches the ambient temperature inside the refrigerator. The graph of the temperature function is shown in Figure 3.
■ Continuously Compounded Interest EXAMPLE 4 If $5000 is invested at 2% interest, compounded annually, then after 1 year the investment is worth $5000s1.02d − $5100.00, after 2 years it’s worth [$5000s1.02d]s1.02d − $5202.00, and after t years it’s worth $5000s1.02dt. In general, if an amount A0 is invested at an interest rate r (r − 0.02 in this example), then after t years it’s worth A0s1 1 rdt. Usually, interest is compounded more frequently, say, n times per year. Then in each compounding period the rate is ryn, and there are nt compounding periods in t years, so the value of the investment is
S D
A − A0 1 1
r n
nt
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CHAPTER 3 Differentiation Rules
For instance, after 3 years at 2% interest a $5000 investment will be worth $5000s1.02d3 − $5306.04 with annual compounding $5000s1.01d6 − $5307.60 with semiannual compounding $5000s1.005d12 − $5308.39 with quarterly compounding
S
$5000 1 1
S
$5000 1 1
0.02 12
0.02 365
D
D
36
− $5308.92 with monthly compounding
365?3
− $5309.17 with daily compounding
You can see that the interest paid increases as the number of compounding periods snd increases. If we let n l `, then we will be compounding the interest continuously and the value of the investment will be
S FS F S F S
Astd − lim A0 1 1 nl`
r n
− A0 lim
11
r n
− A0 lim
11
1 m
ml `
nl`
S D 11
1 n
n
DG DG DG
11
nl`
e − lim
D
nt
− lim A0 nl`
Equation 3.6.6:
r n
nyr
rt
nyr
rt
m
rt
(where m − nyr)
But the limit in this expression is equal to the number e (see Equation 3.6.6). So with continuous compounding of interest at interest rate r, the amount after t years is Astd − A0 e rt If we differentiate this equation, we get dA − rA0 e rt − rAstd dt which says that, with continuous compounding of interest, the rate of increase of an investment is proportional to its size. Returning to the example of $5000 invested for 3 years at 2% interest, we see that with continuously compounding of interest the value of the investment will be As3d − $5000es0.02d3 − $5309.18 Notice how close this is to the amount we calculated for daily compounding, $5309.17. But the amount is easier to compute if we use continuous compounding. ■
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SECTION 3.8 Exponential Growth and Decay
245
3.8 Exercises 1. A population of the yeast cell Saccharomyces cerevisiae (a yeast used for fermentation) develops with a constant relative growth rate of 0.4159 per hour. The initial population consists of 3.8 million cells. Find the population size after 2 hours. 2. A common inhabitant of human intestines is the bacterium Escherichia coli, named after the German pediatrician Theodor Escherich, who identified it in 1885. A cell of this bacterium in a nutrientbroth medium divides into two cells every 20 minutes. The initial population of a culture is 50 cells. (a) Find the relative growth rate. (b) Find an expression for the number of cells after t hours. (c) Find the number of cells after 6 hours. (d) Find the rate of growth after 6 hours. (e) When will the population reach a million cells? 3. A culture of the bacterium Salmonella enteritidis initially contains 50 cells. When introduced into a nutrient broth, the culture grows at a rate proportional to its size. After 1.5 hours the population has increased to 975. (a) Find an expression for the number of bacteria after t hours. (b) Find the number of bacteria after 3 hours. (c) Find the rate of growth after 3 hours. (d) After how many hours will the population reach 250,000 ? 4. A bacteria culture grows with constant relative growth rate. The bacteria count was 400 after 2 hours and 25,600 after 6 hours. (a) What is the relative growth rate? Express your answer as a percentage. (b) What was the initial size of the culture? (c) Find an expression for the number of bacteria after t hours. (d) Find the number of bacteria after 4.5 hours. (e) Find the rate of growth after 4.5 hours. (f ) When will the population reach 50,000 ? 5. The table gives estimates of the world population, in millions, from 1750 to 2000.
(b) Use the exponential model and the population figures for 1850 and 1900 to predict the world population in 1950. Compare with the actual population. (c) Use the exponential model and the population figures for 1900 and 1950 to predict the world population in 2000. Compare with the actual population and try to explain the discrepancy.
6. The table gives census data for the population of Indonesia, in millions, during the second half of the 20th century.
Year
Population (millions)
1950
83
1960
100
1970
122
1980
150
1990
182
2000
214
(a) Assuming the population grows at a rate proportional to its size, use the census data for 1950 and 1960 to predict the population in 1980. Compare with the actual figure. (b) Use the census data for 1960 and 1980 to predict the population in 2000. Compare with the actual population. (c) Use the census data for 1980 and 2000 to predict the population in 2010 and compare with the actual population of 243 million. (d) Use the model in part (c) to predict the population in 2025. Do you think the prediction will be too high or too low? Why?
7. Experiments show that if the chemical reaction
N2O5 l 2NO 2 1 12 O 2 Year
Population (millions)
Year
Population (millions)
1750 1800 1850
790 980 1260
1900 1950 2000
1650 2560 6080
takes place at 45 8C, the rate of reaction of dinitrogen pentoxide is proportional to its concentration as follows:
2
(a) Use the exponential model and the population figures for 1750 and 1800 to predict the world population in 1900 and 1950. Compare with the actual figures.
dfN2O5g − 0.0005fN2O5g dt
(a) Find an expression for the concentration fN2O5g after t seconds if the initial concentration is C. (b) How long will the reaction take to reduce the concentration of N2O5 to 90% of its original value?
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246
CHAPTER 3 Differentiation Rules
8. Strontium90 has a halflife of 28 days. (a) A sample has initial mass 50 mg. Find a formula for the mass remaining after t days. (b) Find the mass remaining after 40 days. (c) How long does it take the sample to decay to a mass of 2 mg? (d) Sketch the graph of the mass function. 9. The halflife of cesium137 is 30 years. Suppose we have a 100mg sample. (a) Find the mass that remains after t years. (b) How much of the sample remains after 100 years? (c) After how long will only 1 mg remain? 10. A sample of einsteinium252 decayed to 64.3% of its original mass after 300 days. (a) What is the halflife of einsteinium252? (b) How long would it take the sample to decay to onethird of its original mass? 11–13 Radiocarbon Dating Scientists can determine the age of ancient objects by the method of radiocarbon dating. The bombardment of the upper atmosphere by cosmic rays converts nitrogen to a radioactive isotope of carbon, 14 C, with a halflife of about 5730 years. Vegetation absorbs carbon dioxide through the atmosphere and animal life assimilates 14 C through food chains. When a plant or animal dies, it stops replacing its carbon and the amount of 14 C present begins to decrease through radioactive decay. Therefore the level of radioactivity must also decay exponentially. 11. A discovery revealed a parchment fragment that had about 74% as much 14 C radioactivity as does plant material on the earth today. Estimate the age of the parchment. 12. D inosaur fossils are too old to be reliably dated using carbon14. Suppose we had a 68millionyearold dinosaur fossil. What fraction of the living dinosaur’s 14 C would be remaining today? Suppose the minimum detectable mass is 0.1%. What is the maximum age of a fossil that could be dated using 14 C?
15. A roast turkey is removed from an oven when its temperature has reached 85°C and is placed on a table in a room where the ambient temperature is 22°C. (a) If the temperature of the turkey is 65 8C after half an hour, what is the temperature after 45 minutes? (b) When will the turkey have cooled to 40 8C ? 16. I n a murder investigation, the temperature of the corpse was 32.5°C at 1:30 pm and 30.3°C an hour later. Normal body temperature is 37.0°C and the ambient temperature was 20.0°C. When did the murder take place? 17. W hen a cold drink is taken from a refrigerator, its temperature is 5°C. After 25 minutes in a 20°C room its temperature has increased to 10°C. (a) What is the temperature of the drink after 50 minutes? (b) When will its temperature reach 15°C? 18. A freshly brewed cup of coffee has temperature 958C in a 20°C room. When its temperature is 70°C, it is cooling at a rate of 1°C per minute. When does this occur? 19. T he rate of change of atmospheric pressure P with respect to altitude h is proportional to P, provided that the temperature is constant. At 15°C the pressure is 101.3 kPa at sea level and 87.14 kPa at h − 1000 m. (a) What is the pressure at an altitude of 3000 m? (b) What is the pressure at the top of Mount McKinley, at an altitude of 6187 m? 20. (a) If $2500 is borrowed at 4.5% interest, find the amounts due at the end of 3 years if the interest is compounded (i) annually, (ii) quarterly, (iii) monthly, (iv) weekly, (v) daily, (vi) hourly, and (vii) continuously. (b) Suppose $2500 is borrowed and the interest is ; compounded continuously. If Astd is the amount due after t years, where 0 < t < 3, graph Astd for each of the interest rates 5%, 6%, and 7% on a common screen.
13. D inosaur fossils are often dated by using an element other than carbon, such as potassium40, that has a longer halflife (in this case, approximately 1.25 billion years). Suppose the minimum detectable mass is 0.1% and a dinosaur is dated with 40 K to be 68 million years old. Is such a dating possible? In other words, what is the maximum age of a fossil that could be dated using 40 K?
21. (a) If $4000 is invested at 1.75% interest, find the value of the investment at the end of 5 years if the interest is com pounded (i) annually, (ii) semiannually, (iii) monthly, (iv) weekly, (v) daily, and (vi) continuously. (b) If Astd is the amount of the investment at time t for the case of continuous compounding, write a differential equation and an initial condition satisfied by Astd.
14. A curve passes through the point s0, 5d and has the property that the slope of the curve at every point P is twice the ycoordinate of P. What is the equation of the curve?
22. (a) How long will it take an investment to double in value if the interest rate is 3%, compounded continuously? (b) What is the equivalent annual interest rate?
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SECTION 3.9 Related Rates
247
APPLIED PROJECT CONTROLLING RED BLOOD CELL LOSS DURING SURGERY A typical volume of blood in the human body is about 5 L . A certain percentage of that volume (called the hematocrit) consists of red blood cells (RBCs); typically the hematocrit is about 45% in males. Suppose that a surgery takes four hours and a male patient bleeds 2.5 L of blood. During surgery the patient’s blood volume is maintained at 5 L by injection of saline solution, which mixes quickly with the blood but dilutes it so that the hematocrit decreases as time passes. 1. Assuming that the rate of RBC loss is proportional to the volume of RBCs, determine the patient’s volume of RBCs by the end of the operation.
Ken Weakley Kent Weakley//Shutterstock.com Shutterstock.com
2. A procedure called acute normovolemic hemodilution (ANH) has been developed to minimize RBC loss during surgery. In this procedure blood is extracted from the patient before the operation and replaced with saline solution. This dilutes the patient’s blood, resulting in fewer RBCs being lost by bleeding during surgery. The extracted blood is then returned to the patient after surgery. Only a certain amount of blood can be extracted, however, because the RBC concentration can never be allowed to drop below 25% during surgery. What is the maximum amount of blood that can be extracted in the ANH procedure for the surgery described in this project? 3. What is the RBC loss without the ANH procedure? What is the loss if the procedure is carried out with the volume calculated in Problem 2?
3.9 Related Rates If we are pumping air into a balloon, both the volume and the radius of the balloon are increasing and their rates of increase are related to each other. But it is much easier to measure directly the rate of increase of the volume than the rate of increase of the radius. In a related rates problem the idea is to compute the rate of change of one quantity in terms of the rate of change of another quantity (which may be more easily measured). The procedure is to find an equation that relates the two quantities and then use the Chain Rule to differentiate both sides with respect to time.
EXAMPLE 1 Air is being pumped into a spherical balloon so that its volume increases at a rate of 100 cm3ys. How fast is the radius of the balloon increasing when the diameter is 50 cm? PS According to the Principles of Problem
Solving discussed following Chapter 1, the first step is to understand the problem. This includes reading the problem carefully, identifying the given and the unknown, and introducing suitable notation.
SOLUTION We start by identifying two things: the given information: the rate of increase of the volume of air is 100 cm3ys and the unknown: the rate of increase of the radius when the diameter is 50 cm In order to express these quantities mathematically, we introduce some suggestive notation: Let V be the volume of the balloon and let r be its radius.
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CHAPTER 3 Differentiation Rules
The key thing to remember is that rates of change are derivatives. In this problem, the volume and the radius are both functions of the time t. The rate of increase of the volume with respect to time is the derivative dVydt, and the rate of increase of the radius is drydt. We can therefore restate the given and the unknown as follows: dV − 100 cm3ys dt dr when r − 25 cm dt
Given: Unknown:
In order to connect dVydt and drydt, we first relate V and r by a formula—in this case, the formula for the volume of a sphere: V − 43 r 3 PS The second stage of problem solving is to
think of a plan for connecting the given and the unknown.
In order to use the given information, we differentiate each side of this equation with respect to t. To differentiate the right side, we need to use the Chain Rule: dV dV dr dr − − 4r 2 dt dr dt dt Now we solve for the unknown quantity: dr 1 dV − dt 4r 2 dt
Notice that, although dVydt is con stant, drydt is not constant.
If we put r − 25 and dVydt − 100 in this equation, we obtain dr 1 1 − 2 100 − dt 4s25d 25 The radius of the balloon is increasing at the rate of 1ys25d < 0.0127 cmys when the diameter is 50 cm. ■
wall
EXAMPLE 2 A ladder 5 m long rests against a vertical wall. If the bottom of the ladder slides away from the wall at a rate of 1 mys, how fast is the top of the ladder sliding down the wall when the bottom of the ladder is 3 m from the wall?
5
y
x
ground
FIGURE 1
SOLUTION We first draw a diagram and label it as in Figure 1. Let x meters be the distance from the bottom of the ladder to the wall and y meters the distance from the top of the ladder to the ground. Note that x and y are both functions of t (time, measured in seconds). We are given that dxydt − 1 mys and we are asked to find dyydt when x − 3 m (see Figure 2). In this problem, the relationship between x and y is given by the Pythagorean Theorem: x 2 1 y 2 − 25 Differentiating each side with respect to t using the Chain Rule, we have
dy dt
2x
=?
Solving this equation for the desired rate, we obtain
y
dy x dx −2 dt y dt
x dx dt
FIGURE 2
dx dy 1 2y −0 dt dt
=1
When x − 3, the Pythagorean Theorem gives y − 4 and so, substituting these values and dxydt − 1, we have dy 3 − 2 s1d − 20.75 mys dt 4
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SECTION 3.9 Related Rates
249
The fact that dyydt is negative means that the distance from the top of the ladder to the ground is decreasing at a rate of 0.75 mys. In other words, the top of the ladder is sliding down the wall at a rate of 0.75 mys. ■ PS Look back: What have we learned from
Examples 1 and 2 that will help us solve future problems?
WARNING A common error is to substitute the given numerical information (for quantities that vary with time) too early. This should be done only after the differentiation. (Step 7 follows Step 6.) For instance, in Example 1 we dealt with general values of r until we finally substituted r − 25 at the last step. (If we had put r − 25 earlier, we would have gotten dVydt − 0, which is clearly wrong.)
Problem Solving Strategy It is useful to recall some of the problemsolving principles and adapt them to related rates in light of our experience in Examples 1 and 2: 1. Read the problem carefully. 2. Draw a diagram if possible. 3. Introduce notation. Assign symbols to all quantities that are functions of time. 4. Express the given information and the required rate in terms of derivatives. 5. Write an equation that relates the various quantities of the problem. If necessary, use the geometry of the situation to eliminate one of the variables by substitution (see Example 3 below). 6. Use the Chain Rule to differentiate both sides of the equation with respect to t. 7. Substitute the given information into the resulting equation and solve for the unknown rate. See also Principles of Problem Solving following Chapter 1.
The following examples further illustrate this strategy.
EXAMPLE 3 A water tank has the shape of an inverted circular cone with base radius 2 m and height 4 m. If water is being pumped into the tank at a rate of 2 m 3ymin, find the rate at which the water level is rising when the water is 3 m deep.
2
r
4 h
SOLUTION We first sketch the cone and label it as in Figure 3. Let V, r, and h be the volume of the water, the radius of the surface, and the height of the water at time t, where t is measured in minutes. We are given that dVydt − 2 m 3ymin and we are asked to find dhydt when h is 3 m. The quantities V and h are related by the equation V − 13 r 2h
FIGURE 3
but it is very useful to express V as a function of h alone. In order to eliminate r, we use the similar triangles in Figure 3 to write r 2 h − r − h 4 2 and the expression for V becomes V−
SD
1 h 3 2
2
h−
3 h 12
Now we can differentiate each side with respect to t : dV 2 dh − h dt 4 dt so
dh 4 dV − dt h 2 dt
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250
CHAPTER 3 Differentiation Rules
Substituting h − 3 m and dVydt − 2 m 3ymin, we have dh 4 8 − 2 2 − dt s3d 9 The water level is rising at a rate of 8ys9d < 0.28 mymin.
■
EXAMPLE 4 Car A is traveling west at 80 kmyh and car B is traveling north at 100 kmyh. Both are headed for the intersection of the two roads. At what rate are the cars approaching each other when car A is 0.3 km and car B is 0.4 km from the intersection? x
C y
z
B
A
SOLUTION We draw Figure 4, where C is the intersection of the roads. At a given time t, let x be the distance from car A to C, let y be the distance from car B to C, and let z be the distance between the cars, where x, y, and z are measured in miles. We are given that dxydt − 280 kmyh and dyydt − 2700 kmyh. (The derivatives are negative because x and y are decreasing.) We are asked to find dzydt. The equation that relates x, y, and z is given by the Pythagorean Theorem: z2 − x 2 1 y 2
FIGURE 4
Differentiating each side with respect to t, we have 2z
dz dx dy − 2x 1 2y dt dt dt dz 1 − dt z
S
x
dx dy 1y dt dt
D
When x − 0.3 km and y − 0.4 km, the Pythagorean Theorem gives z − 0.5 km, so dz 1 − f0.3s280d 1 0.4s2100dg − 2128 kmyh dt 0.5 The cars are approaching each other at a rate of 128 kmyh.
■
EXAMPLE 5 A man walks along a straight path at a speed of 1 mys. A spotlight is located on the ground 6 m from the path and is kept focused on the man. At what rate is the spotlight rotating when the man is 4.5 m from the point on the path closest to the light? SOLUTION We draw Figure 5 and let x be the distance from the man to the point on the path closest to the spotlight. We let be the angle between the beam of the light and the perpendicular to the path. We are given that dxydt − 1 mys and are asked to find dydt when x − 4.5. The equation that relates x and can be written from Figure 5: x
6 ¨
x − tan x − 6 tan 6 Differentiating each side with respect to t, we get dx d − 6 sec2 dt dt
FIGURE 5
so
d 1 dx − cos2 dt 6 dt −
1 1 cos2 s1d − cos2 6 6
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SECTION 3.9 Related Rates
251
4 When x − 4.5, the length of the beam is 7.5, so cos − 20 25 − 5 and
d 1 − dt 6
rad 1 rotation 60 s 0.107 3 3 s 2 rad 1 min < 1.02 rotations per min
SD 4 5
2
−
16 − 0.107 150
The spotlight is rotating at a rate of 0.107 radys.
■
3.9 Exercises 1. (a) If V is the volume of a cube with edge length x and the cube expands as time passes, find dVydt in terms of dxydt. (b) If the length of the edge of a cube is increasing at a rate of 4 cmys, how fast is the volume of the cube increasing when the edge length is 15 cm? 2. (a) If A is the area of a circle with radius r and the circle expands as time passes, find dAydt in terms of drydt. (b) Suppose oil spills from a ruptured tanker and spreads in a circular pattern. If the radius of the oil spill increases at a constant rate of 2 mys, how fast is the area of the spill increasing when the radius is 30 m? 3. Each side of a square is increasing at a rate of 6 cmys. At what rate is the area of the square increasing when the area of the square is 16 cm2 ? 4. The radius of a sphere is increasing at a rate of 4 mmys. How fast is the volume increasing when the diameter is 80 mm? 5. The radius of a spherical ball is increasing at a rate of 2 cmymin. At what rate is the surface area of the ball increasing when the radius is 8 cm? 6. The length of a rectangle is increasing at a rate of 8 cmys and its width is increasing at a rate of 3 cmys. When the length is 20 cm and the width is 10 cm, how fast is the area of the rectangle increasing? 7. A cylindrical tank with radius 5 m is being filled with water at a rate of 3 m3ymin. How fast is the height of the water increasing? 8. The area of a triangle with sides of lengths a and b and contained angle is A − 12 ab sin . (See Formula 6 in Appendix D.) (a) If a − 2 cm, b − 3 cm, and increases at a rate of 0.2 radymin, how fast is the area increasing when − y3? (b) If a − 2 cm, b increases at a rate of 1.5 cmymin, and increases at a rate of 0.2 radymin, how fast is the area increasing when b − 3 cm and − y3? (c) If a increases at a rate of 2.5 cmymin, b increases at a rate of 1.5 cmymin, and increases at a rate of 0.2 radymin, how fast is the area increasing when a − 2 cm, b − 3 cm, and − y3?
9. Suppose 4x 2 1 9y 2 − 25, where x and y are functions of t. (a) If dyydt − 13, find dxydt when x − 2 and y − 1. (b) If dxydt − 3, find dy ydt when x − 22 and y − 1. 10. If x 2 1 y 2 1 z 2 − 9, dxydt − 5, and dyydt − 4, find dzydt when sx, y, zd − s2, 2, 1d. 11. The weight w of an astronaut (in newtons) is related to her height h above the surface of the earth (in kilometers) by
S
w − w0
6370 6370 1 h
D
2
where w0 is the weight of the astronaut on the surface of the earth. If the astronaut weighs 580 newtons on earth and is in a rocket, being propelled upward at a speed of 19 kmys, find the rate at which her weight is changing (in Nys) when she is 60 kilometers above the earth’s surface. 12. A particle is moving along a hyperbola xy − 8. As it reaches the point s4, 2d, the ycoordinate is decreasing at a rate of 3 cmys. How fast is the xcoordinate of the point changing at that instant? 13–16 (a) What quantities are given in the problem? (b) What is the unknown? (c) Draw a picture of the situation for any time t. (d) Write an equation that relates the quantities. (e) Finish solving the problem. 13. A plane flying horizontally at an altitude of 2 km and a speed of 800 kmyh passes directly over a radar station. Find the rate at which the distance from the plane to the station is increasing when the plane is 3 km away from the station. 14. If a snowball melts so that its surface area decreases at a rate of 1 cm2ymin, find the rate at which the diameter decreases when the diameter is 10 cm. 15. A street light is mounted at the top of a 6metertall pole. A man 2 m tall walks away from the pole with a speed of 1.5 mys along a straight path. How fast is the tip of his shadow moving when he is 10 m from the pole? 16. At noon, ship A is 150 km west of ship B. Ship A is sailing east at 35 kmyh and ship B is sailing north at 25 kmyh. How fast is the distance between the ships changing at 4:00 pm?
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252
CHAPTER 3 Differentiation Rules
17. T wo cars start moving from the same point. One travels south at 30 kmyh and the other travels west at 72 kmyh. At what rate is the distance between the cars increasing two hours later? 18. A spotlight on the ground shines on a wall 12 m away. If a man 2 m tall walks from the spotlight toward the building at a speed of 1.6 mys, how fast is the length of his shadow on the building decreasing when he is 4 m from the building? 19. A man starts walking north at 1.2 mys from a point P. Five minutes later a woman starts walking south at 1.6 mys from a point 200 m due east of P. At what rate are the people moving apart 15 min after the woman starts walking? 20. A baseball diamond is a square with side 18 m. A batter hits the ball and runs toward first base with a speed of 7.5 mys. (a) At what rate is his distance from second base decreasing when he is halfway to first base? (b) At what rate is his distance from third base increasing at the same moment?
18 m
25. W ater is leaking out of an inverted conical tank at a rate of 10,000 cm 3ymin at the same time that water is being pumped into the tank at a constant rate. The tank has height 6 m and the diameter at the top is 4 m. If the water level is rising at a rate of 20 cmymin when the height of the water is 2 m, find the rate at which water is being pumped into the tank. 26. A particle moves along the curve y − 2 sinsxy2d. As the particle passes through the point ( 13 , 1), its xcoordinate increases at a rate of s10 cmys. How fast is the distance from the particle to the origin changing at this instant? 27. A water trough is 10 m long and a crosssection has the shape of an isosceles trapezoid that is 30 cm wide at the bottom, 80 cm wide at the top, and has height 50 cm. If the trough is being filled with water at the rate of 0.2 m 3ymin, how fast is the water level rising when the water is 30 cm deep? 28. A trough is 6 m long and its ends have the shape of isosceles triangles that are 1 m across at the top and have a height of 50 cm. If the trough is being filled with water at a rate of 1.2 m 3ymin, how fast is the water level rising when the water is 30 centimeters deep? 29. G ravel is being dumped from a conveyor belt at a rate of 3 m 3ymin, and its coarseness is such that it forms a pile in the shape of a cone whose base diameter and height are always equal. How fast is the height of the pile increasing when the pile is 3 m high?
21. T he altitude of a triangle is increasing at a rate of 1 cmymin while the area of the triangle is increasing at a rate of 2 cm 2ymin. At what rate is the base of the triangle changing when the altitude is 10 cm and the area is 100 cm2 ? 22. A boat is pulled into a dock by a rope attached to the bow of the boat and passing through a pulley on the dock that is 1 m higher than the bow of the boat. If the rope is pulled in at a rate of 1 mys, how fast is the boat approaching the dock when it is 8 m from the dock?
23–24 Use the fact that the distance (in meters) a dropped stone falls after t seconds is d − 4.9t 2.
30. A swimming pool is 5 m wide, 10 m long, 1 m deep at the shallow end, and 3 m deep at its deepest point. A crosssection is shown in the Large figure.size If the pool is being filled at a rate of is preferable: 0.1 m 3ymin, how fast is the water level rising when the depth at the deepest point is 1 m?
23. A woman stands near the edge of a cliff and drops a stone over the edge. Exactly one second later she drops another stone. One second after that, how fast is the distance between the two stones changing? 24. Two men stand 10 m apart on level ground near the edge of a cliff. One man drops a stone and one second later the other man drops a stone. One second after that, how fast is the distance between the two stones changing?
1 2 1.5
3
4
1.5
31. T he sides of an equilateral triangle are increasing at a rate of 10 cmymin. At what rate is the area of the triangle increasing when the sides are 30 cm long?
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3
SECTION 3.9 Related Rates
32. A kite 50 m above the ground moves horizontally at a speed of 2 mys. At what rate is the angle between the string and the horizontal decreasing when 100 m of string has been let out? 33. A car is traveling north on a straight road at 20 mys and a drone is flying east at 6 mys at an elevation of 25 m. At one instant the drone passes directly over the car. How fast is the distance between the drone and the car changing 5 seconds later? 34. I f the minute hand of a clock has length r (in centimeters), find the rate at which it sweeps out area as a function of r. 35. H ow fast is the angle between the ladder and the ground changing in Example 2 when the bottom of the ladder is 3 m from the wall? 36. A ccording to the model we used to solve Example 2, what happens as the top of the ladder approaches the ground? Is the model appropriate for small values of y? 37. B oyle’s Law states that when a sample of gas is compressed at a constant temperature, the pressure P and volume V satisfy the equation PV − C , where C is a constant. Suppose that at a certain instant the volume is 600 cm3, the pressure is 150 kPa, and the pressure is increasing at a rate of 20 kPaymin. At what rate is the volume decreasing at this instant? faucet is filling a hemispherical basin of diameter 60 cm ; 38. A with water at a rate of 2 Lymin. Find the rate at which the water is rising in the basin when it is half full. [Use the following facts: 1 L is 1000 cm3. The volume of the portion of a sphere with radius r from the bottom to a height h is V − (rh 2 2 13 h 3), as we will show in Chapter 6.] 39. I f two resistors with resistances R1 and R2 are connected in parallel, as shown in the figure, then the total resistance R, measured in ohms (V), is given by 1 1 1 − 1 R R1 R2 If R1 and R2 are increasing at rates of 0.3 Vys and 0.2 Vys, respectively, how fast is R changing when R1 − 80 V and R2 − 100 V?
R¡
R™
40. W hen air expands adiabatically (without gaining or losing heat), its pressure P and volume V are related by the equation PV 1.4 − C , where C is a constant. Suppose that at a certain instant the volume is 400 cm3 and the pressure is 80 kPa and is decreasing at a rate of 10 kPaymin. At what rate is the volume increasing at this instant?
253
41. Two straight roads diverge from an intersection at an angle of 60°. Two cars leave the intersection at the same time, the first traveling down one road at 60 kmyh and the second traveling down the other road at 100 kmyh. How fast is the distance between the cars changing after half an hour? [Hint: Use the Law of Cosines (Formula 21 in Appendix D).] 42. B rain weight B as a function of body weight W in fish has been modeled by the power function B − 0.007W 2y3, where B and W are measured in grams. A model for body weight as a function of body length L (measured in centimeters) is W − 0.12L2.53. If, over 10 million years, the average length of a certain species of fish evolved from 15 cm to 20 cm at a constant rate, how fast was this species’ brain growing when its average length was 18 cm? 43. T wo sides of a triangle have lengths 12 m and 15 m. The angle between them is increasing at a rate of 2 8ymin. How fast is the length of the third side increasing when the angle between the sides of fixed length is 60°? [Hint: Use the Law of Cosines (Formula 21 in Appendix D).] 44. T wo carts, A and B, are connected by a rope 12 m long that passes over a pulley P. (See the figure.) The point Q is on the floor 4 m directly beneath P and between the carts. Cart A is being pulled away from Q at a speed of 0.5 mys. How fast is cart B moving toward Q at the instant when cart A is 3 m from Q ?
P 4m A
B Q
45. A television camera is positioned 1200 m from the base of a rocket launching pad. The angle of elevation of the camera has to change at the correct rate in order to keep the rocket in sight. Also, the mechanism for focusing the camera has to take into account the increasing distance from the camera to the rising rocket. Let’s assume the rocket rises vertically and its speed is 200 mys when it has risen 900 m. (a) How fast is the distance from the television camera to the rocket changing at that moment? (b) If the television camera is always kept aimed at the rocket, how fast is the camera’s angle of elevation changing at that same moment? 46. A lighthouse is located on a small island 3 km away from the nearest point P on a straight shoreline and its light makes four revolutions per minute. How fast is the beam of light moving along the shoreline when it is 1 km from P ? 47. A plane flies horizontally at an altitude of 5 km and passes directly over a tracking telescope on the ground. When the
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254
CHAPTER 3 Differentiation Rules
angle of elevation is y3, this angle is decreasing at a rate of y6 radymin. How fast is the plane traveling at that time? 48. A Ferris wheel with a radius of 10 m is rotating at a rate of one revolution every 2 minutes. How fast is a rider rising when his seat is 16 m above ground level? 49. A plane flying with a constant speed of 300 kmyh passes over a ground radar station at an altitude of 1 km and climbs at an angle of 308. At what rate is the distance from the plane to the radar station increasing a minute later? 50. T wo people start from the same point. One walks east at 4 kmyh and the other walks northeast at 2 kmyh. How fast is the distance between the people changing after 15 minutes?
3.10
51. A runner sprints around a circular track of radius 100 m at a constant speed of 7 mys. The runner’s friend is standing at a distance 200 m from the center of the track. How fast is the distance between the friends changing when the distance between them is 200 m? 52. T he minute hand on a watch is 8 mm long and the hour hand is 4 mm long. How fast is the distance between the tips of the hands changing at one o’clock? 53. Suppose that the volume V of a rolling snowball increases so that dVydt is proportional to the surface area of the snowball at time t. Show that the radius r increases at a constant rate, that is, drydt is constant.
Linear Approximations and Differentials We have seen that a curve lies very close to its tangent line near the point of tangency. In fact, by zooming in toward a point on the graph of a differentiable function, we noticed that the graph looks more and more like its tangent line. (See Figure 2.7.2.) This observation is the basis for a method of finding approximate values of functions.
■ Linearization and Approximation y
It might be easy to calculate a value f sad of a function, but difficult (or even impossible) to compute nearby values of f . So we settle for the easily computed values of the linear function L whose graph is the tangent line of f at sa, f sadd. (See Figure 1.) In other words, we use the tangent line at sa, f sadd as an approximation to the curve y − f sxd when x is near a. An equation of this tangent line is
y=ƒ
{a, f(a)}
y=L(x)
y − f sad 1 f 9sadsx 2 ad The linear function whose graph is this tangent line, that is, x
0
FIGURE 1
1
Lsxd − f sad 1 f 9sadsx 2 ad
is called the linearization of f at a. The approximation f sxd < Lsxd or 2
f sxd < f sad 1 f 9sadsx 2 ad
is called the linear approximation or tangent line approximation of f at a.
EXAMPLE 1 Find the linearization of the function f sxd − sx 1 3 at a − 1 and use it to approximate the numbers s3.98 and s4.05 . Are these approximations overestimates or underestimates? SOLUTION The derivative of f sxd − sx 1 3d1y2 is f 9sxd − 12 sx 1 3d21y2 − and so we have f s1d − 2 and f 9s1d −
1 4.
1 2sx 1 3
Putting these values into Equation 1, we see
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SECTION 3.10 Linear Approximations and Differentials
255
that the linearization is Lsxd − f s1d 1 f 9s1dsx 2 1d − 2 1 14 sx 2 1d −
7 x 1 4 4
The corresponding linear approximation (2) is sx 1 3
1
5
tanh21x − 12 ln
S D 11x 12x
21 , x , 1
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SECTION 3.11 Hyperbolic Functions
265
EXAMPLE 3 Show that sinh21x − ln( x 1 sx 2 1 1 ). SOLUTION Let y − sinh21x. Then x − sinh y −
e y 2 e2y 2
so
e y 2 2x 2 e2y − 0
or, multiplying by e y,
e 2y 2 2xe y 2 1 − 0
This is really a quadratic equation in e y: se y d2 2 2xse y d 2 1 − 0 Solving by the quadratic formula, we get ey −
2x 6 s4x 2 1 4 − x 6 sx 2 1 1 2
Note that e y . 0, but x 2 sx 2 1 1 , 0 (because x , sx 2 1 1 ). Thus the minus sign is inadmissible and we have e y − x 1 sx 2 1 1 Therefore This shows that
y − lnse y d − ln( x 1 sx 2 1 1 ) sinh21x − ln( x 1 sx 2 1 1 )
(See Exercise 29 for another method.)
Notice that the formulas for the derivatives of tanh21x and coth21x appear to be identical. But the domains of these functions have no numbers in common: tanh21x is defined for x , 1, whereas coth21x is defined for x . 1.
   
■
6 Derivatives of Inverse Hyperbolic Functions d 1 d 1 ssinh21xd − scsch21xd − 2 2 dx dx x sx 2 1 1 s1 1 x
 
d 1 scosh21xd − 2 dx sx 2 1
d 1 ssech21xd − 2 dx x s1 2 x 2
d 1 stanh21xd − dx 1 2 x2
d 1 scoth21xd − dx 1 2 x2
The inverse hyperbolic functions are all differentiable because the hyperbolic functions are differentiable (see Appendix F ). The formulas in Table 6 can be proved either by the method for inverse functions or by differentiating Formulas 3, 4, and 5.
EXAMPLE 4 Prove that
d 1 ssinh21xd − . dx s1 1 x 2
SOLUTION 1 Let y − sinh21x. Then sinh y − x. If we differentiate this equation implicitly with respect to x, we get cosh y
dy −1 dx
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266
CHAPTER 3 Differentiation Rules
Since cosh2 y 2 sinh2 y − 1 and cosh y > 0, we have cosh y − s1 1 sinh2 y , so dy 1 1 1 − − − dx cosh y s1 1 sinh2 y s1 1 x 2 SOLUTION 2 From Equation 3 (proved in Example 3), we have d d ssinh21xd − ln( x 1 sx 2 1 1 ) dx dx − −
− −
EXAMPLE 5 Find
1 d ( x 1 sx 2 1 1 ) x 1 sx 2 1 1 dx 1 x 1 sx 1 1 2
S
11
x sx 1 1 2
D
sx 2 1 1 1 x
(x 1 sx 2 1 1 )sx 2 1 1 1 sx 2 1 1
■
d ftanh21ssin xdg. dx
SOLUTION Using Table 6 and the Chain Rule, we have d 1 d ftanh21ssin xdg − ssin xd dx 1 2 ssin xd2 dx −
1 cos x − sec x 2 cos x − 1 2 sin x cos2x
■
3.11 Exercises 1–6 Find the numerical value of each expression.
9. Write sinhsln xd as a rational function of x.
cosh 0 1. (a) sinh 0 (b)
10. Write coshs4 ln xd as a rational function of x .
2. (a) tanh 0 (b) tanh 1
11–23 Prove the identity.
3. (a) coshsln 5d (b) cosh 5
11. sinhs2xd − 2sinh x (This shows that sinh is an odd function.)
4. (a) sinh 4 (b) sinhsln 4d 5. (a) sech 0 (b) cosh21 1
12. coshs2xd − cosh x (This shows that cosh is an even function.)
6. (a) sinh 1 (b) sinh21 1
13. cosh x 1 sinh x − e x 14. cosh x 2 sinh x − e2x
x
7. Write 8 sinh x 1 5 cosh x in terms of e and e . 8. Write 2e
2x
1 3e
22x
2x
in terms of sinh 2x and cosh 2x.
15. sinhsx 1 yd − sinh x cosh y 1 cosh x sinh y 16. coshsx 1 yd − cosh x cosh y 1 sinh x sinh y
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SECTION 3.11 Hyperbolic Functions
33. Prove the formula given in Table 6 for the derivative of each of the following functions. (a) cosh21 (b) tanh21 (c) coth21
17. coth2x 2 1 − csch2x 18. tanhsx 1 yd −
tanh x 1 tanh y 1 1 tanh x tanh y
34. Prove the formula given in Table 6 for the derivative of each of the following functions. (a) sech21 (b) csch21
19. sinh 2x − 2 sinh x cosh x 20. cosh 2x − cosh 2 x 1 sinh 2 x 21. tanhsln xd −
35–53 Find the derivative. Simplify where possible.
x2 2 1 x2 1 1
35. f sxd − cosh 3x
36. f sxd − e x cosh x
37. hsxd − sinhsx 2 d
38. tsxd − sinh 2 x
23. scosh x 1 sinh xdn − cosh nx 1 sinh nx (n any real number)
39. Gstd − sinhsln td
40. Fstd − lnssinh td
41. f sxd − tanhsx
42. Hsvd − e tanh 2v
24. If tanh x − 12 13 , find the values of the other hyperbolic functions at x.
43. y − sech x tanh x
44. y − sechstanh xd
45. tstd − t coth st 2 1 1
46. f std −
47. f sxd − sinh21s22xd
48. tsxd − tanh21sx 3 d
22.
1 1 tanh x − e 2x 1 2 tanh x
25. If cosh x − 53 and x . 0, find the values of the other hyperbolic functions at x. 26. (a) Use the graphs of sinh, cosh, and tanh in Figures 1–3 to draw the graphs of csch, sech, and coth. (b) Check the graphs that you sketched in part (a) by using ; a graphing calculator or computer to produce them. 27. U se the definitions of the hyperbolic functions to find each of the following limits. (a) lim tanh x (b) lim tanh x xl`
x l2`
(c) lim sinh x (d) lim sinh x xl`
(e) lim sech x xl`
x l2`
(f ) lim coth x
1 1 sinh t 1 2 sinh t
49. y − cosh21ssec d, 0 ⩽ , y2 50. y − sech21ssin d, 0 , , y2 51. Gsud − cosh21s1 1 u 2 , u . 0 52. y − x tanh21x 1 lns1 2 x 2 53. y − x sinh21sxy3d 2 s9 1 x 2
xl`
(g) lim1 coth x (h) lim2 coth x
Î
1 1 tanh x − 12 e xy2. 1 2 tanh x
54. Show that
d dx
28. P rove the formulas given in Table 1 for the derivatives of the functions (a) cosh, (b) tanh, (c) csch, (d) sech, and (e) coth.
55. Show that
d arctanstanh xd − sech 2x. dx
29. G ive an alternative solution to Example 3 by letting y − sinh21x and then using Exercise 13 and Example 1(a) with x replaced by y.
56. T he Gateway Arch The Gateway Arch in St. Louis was designed by Eero Saarinen and was constructed using the equation
x l0
(i) lim csch x x l2`
267
x l0
sinh x ( j) lim xl` ex
y − 211.49 2 20.96 cosh 0.03291765x
30. Prove Equation 4. 31. P rove Equation 5 using (a) the method of Example 3 and (b) Exercise 22 with x replaced by y. 32. F or each of the following functions (i) give a definition like those in (2), (ii) sketch the graph, and (iii) find a formula similar to Equation 3. (a) csch 21 (b) sech21 (c) coth21
4
;
for the central curve of the arch, where x and y are measured in meters and x < 91.20. (a) Graph the central curve. (b) What is the height of the arch at its center? (c) At what points is the height 100 m? (d) What is the slope of the arch at the points in part (c)?
 
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268
CHAPTER 3 Differentiation Rules
57. I f a water wave with length L moves with velocity v in a body of water with depth d, then v−
Î
S D
tL 2d tanh 2 L
where t is the acceleration due to gravity. (See Figure 5.) Explain why the approximation v
0, where b and c are positive constants. (a) Find the velocity and acceleration functions. (b) Show that the particle always moves in the positive direction.
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272
CHAPTER 3 Differentiation Rules
93. A particle moves on a vertical line so that its coordinate at time t is y − t 3 2 12t 1 3, t > 0. (a) Find the velocity and acceleration functions. (b) When is the particle moving upward and when is it moving downward? (c) Find the distance that the particle travels in the time interval 0 < t < 3. (d) Graph the position, velocity, and acceleration functions ; for 0 < t < 3. (e) When is the particle speeding up? When is it slowing down? 1 2 3 r h,
94. T he volume of a right circular cone is V − where r is the radius of the base and h is the height. (a) Find the rate of change of the volume with respect to the height if the radius is constant. (b) Find the rate of change of the volume with respect to the radius if the height is constant. 95. T he mass of part of a wire is x (1 1 sx ) kilograms, where x is measured in meters from one end of the wire. Find the linear density of the wire when x − 4 m. 96. T he cost, in dollars, of producing x units of a certain commodity is
100. A cup of hot chocolate has temperature 80°C in a room kept at 20°C. After half an hour the hot chocolate cools to 60°C. (a) What is the temperature of the chocolate after another half hour? (b) When will the chocolate have cooled to 40°C? 101. T he volume of a cube is increasing at a rate of 10 cm3ymin. How fast is the surface area increasing when the length of an edge is 30 cm? 102. A paper cup has the shape of a cone with height 10 cm and radius 3 cm (at the top). If water is poured into the cup at a rate of 2 cm3ys, how fast is the water level rising when the water is 5 cm deep? 103. A balloon is rising at a constant speed of 2 mys. A boy is cycling along a straight road at a speed of 5 mys. When he passes under the balloon, it is 15 m above him. How fast is the distance between the boy and the balloon increasing 3 s later? 104. A waterskier skis over the ramp shown in the figure at a speed of 10 mys. How fast is she rising as she leaves the ramp?
Csxd − 920 1 2x 2 0.02x 2 1 0.00007x 3
(a) Find the marginal cost function. (b) Find C9s100d and explain its meaning. (c) Compare C9s100d with the cost of producing the 101st item.
97. A bacteria culture contains 200 cells initially and grows at a rate proportional to its size. After half an hour the population has increased to 360 cells. (a) Find the number of cells after t hours. (b) Find the number of cells after 4 hours. (c) Find the rate of growth after 4 hours. (d) When will the population reach 10,000? 98. Cobalt60 has a halflife of 5.24 years. (a) Find the mass that remains from a 100mg sample after 20 years. (b) How long would it take for the mass to decay to 1 mg? 99. Let Cstd be the concentration of a drug in the bloodstream. As the body eliminates the drug, Cstd decreases at a rate that is proportional to the amount of the drug that is present at the time. Thus C9std − 2kCstd, where k is a positive number called the elimination constant of the drug. (a) If C0 is the concentration at time t − 0, find the concentration at time t. (b) If the body eliminates half the drug in 30 hours, how long does it take to eliminate 90% of the drug?
1m 5m
105. The angle of elevation of the sun is decreasing at a rate of 0.25 radyh. How fast is the shadow cast by a 400metertall building increasing when the angle of elevation of the sun is y6? ; 106. (a) Find the linear approximation to f sxd − s25 2 x 2 near 3. (b) Illustrate part (a) by graphing f and the linear approximation. (c) For what values of x is the linear approximation accurate to within 0.1? 3 107. (a) Find the linearization of f sxd − s 1 1 3x at a − 0. State the corresponding linear approximation and use 3 it to give an approximate value for s 1.03 . (b) Determine the values of x for which the linear ; approximation given in part (a) is accurate to within 0.1.
108. Evaluate dy if y − x 3 2 2x 2 1 1, x − 2, and dx − 0.2.
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CHAPTER 3 Review
109. A window has the shape of a square surmounted by a semicircle. The base of the window is measured as having width 60 cm with a possible error in measurement of 0.1 cm. Use differentials to estimate the maximum error possible in computing the area of the window. 110–112 Express the limit as a derivative and evaluate. 17
110. lim
x 21 x21
111. lim
4 16 1 h 2 2 s h
x l1
hl0
113. Evaluate lim
xl0
273
s1 1 tan x 2 s1 1 sin x . x3
114. S uppose f is a differentiable function such that f s tsxdd − x and f 9sxd − 1 1 f f sxdg 2. Show that t9sxd − 1ys1 1 x 2 d. 115. Find f 9sxd if it is known that d f f s2xdg − x 2 dx
112. lim
ly3
cos 2 0.5 2 y3
116. Show that the length of the portion of any tangent line to the astroid x 2y3 1 y 2y3 − a 2y3 cut off by the coordinate axes is constant.
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Problems Plus Try to solve the following examples yourself before reading the solutions. EXAMPLE 1 How many lines are tangent to both of the parabolas y − 21 2 x 2 and y − 1 1 x 2 ? Find the coordinates of the points at which these tangents touch the parabolas. y
SOLUTION To gain insight into this problem, it is essential to draw a diagram. So we sketch the parabolas y − 1 1 x 2 (which is the standard parabola y − x 2 shifted 1 unit upward) and y − 21 2 x 2 (which is obtained by reflecting the first parabola about the xaxis). If we try to draw a line tangent to both parabolas, we soon discover that there are only two possibilities, as illustrated in Figure 1. Let P be a point at which one of these tangents touches the upper parabola and let a be its xcoordinate. (The choice of notation for the unknown is important. Of course we could have used b or c or x 0 or x1 instead of a. However, it’s not advisable to use x in place of a because that x could be confused with the variable x in the equation of the parabola.) Then, since P lies on the parabola y − 1 1 x 2, its ycoordinate must be 1 1 a 2. Because of the symmetry shown in Figure 1, the coordinates of the point Q where the tangent touches the lower parabola must be s2a, 2s1 1 a 2 dd. To use the given information that the line is a tangent, we equate the slope of the line PQ to the slope of the tangent line at P. We have
P 1
x _1
Q
FIGURE 1
mPQ −
1 1 a 2 2 s21 2 a 2 d 1 1 a2 − a 2 s2ad a
If f sxd − 1 1 x 2, then the slope of the tangent line at P is f 9sad − 2a. Thus the condition that we need to use is that 1 1 a2 − 2a a
y
3≈ ≈ 1 ≈ 2
0.3≈ 0.1≈
0
x
y=ln x
FIGURE 2 y
y=c≈ c=?
0
a
y=ln x
FIGURE 3
x
Solving this equation, we get 1 1 a 2 − 2a 2, so a 2 − 1 and a − 61. Therefore the points are (1, 2) and s21, 22d. By symmetry, the two remaining points are s21, 2d and s1, 22d.
■
EXAMPLE 2 For what values of c does the equation ln x − cx 2 have exactly one solution? SOLUTION One of the most important principles of problem solving is to draw a diagram, even if the problem as stated doesn’t explicitly mention a geometric situation. Our present problem can be reformulated geometrically as follows: for what values of c does the curve y − ln x intersect the curve y − cx 2 in exactly one point? Let’s start by graphing y − ln x and y − cx 2 for various values of c. We know that, for c ± 0, y − cx 2 is a parabola that opens upward if c . 0 and downward if c , 0. Figure 2 shows the parabolas y − cx 2 for several positive values of c. Most of them don’t intersect y − ln x at all and one intersects twice. We have the feeling that there must be a value of c (somewhere between 0.1 and 0.3) for which the curves intersect exactly once, as in Figure 3. To find that particular value of c, we let a be the xcoordinate of the single point of intersection. In other words, ln a − ca 2, so a is the unique solution of the given equation. We see from Figure 3 that the curves just touch, so they have a common tangent line when x − a. That means the curves y − ln x and y − cx 2 have the same slope when x − a. Therefore 1 − 2ca a
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Solving the equations ln a − ca 2 and 1ya − 2ca, we get y
ln a − ca 2 − c
y=ln x
Thus a − e 1y2 and
0
x
c−
1 1 − 2c 2
ln a ln e 1y2 1 − − 2 a e 2e
For negative values of c we have the situation illustrated in Figure 4: all parabolas y − cx 2 with negative values of c intersect y − ln x exactly once. And let’s not forget about c − 0: the curve y − 0x 2 − 0 is just the xaxis, which intersects y − ln x exactly once. To summarize, the required values of c are c − 1ys2ed and c < 0. ■
FIGURE 4
Problems
1. Find points P and Q on the parabola y − 1 2 x 2 so that the triangle ABC formed by the xaxis and the tangent lines at P and Q is an equilateral triangle (see the figure). y
A
P
Q 0
B
C
x
3 2 ; 2. Find the point where the curves y − x 2 3x 1 4 and y − 3sx 2 xd are tangent to each other, that is, have a common tangent line. Illustrate by sketching both curves and the common tangent.
3. Show that the tangent lines to the parabola y − ax 2 1 bx 1 c at any two points with xcoordinates p and q must intersect at a point whose xcoordinate is halfway between p and q. 4. Show that
d dx
5. If f sxd − lim tlx
S
sin2 x cos2 x 1 1 1 cot x 1 1 tan x
D
− 2cos 2x.
sec t 2 sec x , find the value of f 9sy4d. t2x
6. Find the values of the constants a and b such that y
lim
xl0
3 ax 1 b 2 2 5 s − x 12
7. Show that sin21stanh xd − tan21ssinh xd.
x
FIGURE FOR PROBLEM 8
8. A car is traveling at night along a highway shaped like a parabola with its vertex at the origin (see the figure). The car starts at a point 100 m west and 100 m north of the origin and travels in an easterly direction. There is a statue located 100 m east and 50 m north of the origin. At what point on the highway will the car’s headlights illuminate the statue? 9. Prove that
dn ssin4 x 1 cos4 xd − 4n21 coss4x 1 ny2d. dx n
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10. If f is differentiable at a, where a . 0, evaluate the following limit in terms of f 9sad: lim
xla
f sxd 2 f sad sx 2 sa
11. The figure shows a circle with radius 1 inscribed in the parabola y − x 2. Find the center of the circle. y
1
y=≈
1 0
x
12. Find all values of c such that the parabolas y − 4x 2 and x − c 1 2y 2 intersect each other at right angles. 13. How many lines are tangent to both of the circles x 2 1 y 2 − 4 and x 2 1 s y 2 3d 2 − 1? At what points do these tangent lines touch the circles? x 46 1 x 45 1 2 14. If f sxd − , calculate f s46ds3d. Express your answer using factorial notation: 11x n! − 1 2 3 ∙ ∙ ∙ sn 2 1d n 15. The figure shows a rotating wheel with radius 40 cm and a connecting rod AP with length 1.2 m. The pin P slides back and forth along the xaxis as the wheel rotates counter clockwise at a rate of 360 revolutions per minute. (a) Find the angular velocity of the connecting rod, dydt, in radians per second, when − y3. (b) Express the distance x − OP in terms of . (c) Find an expression for the velocity of the pin P in terms of .


y
A O
å
¨
P (x, 0) x
16. Tangent lines T1 and T2 are drawn at two points P1 and P2 on the parabola y − x 2 and they intersect at a point P. Another tangent line T is drawn at a point between P1 and P2; it intersects T1 at Q1 and T2 at Q2. Show that
17. Show that
 PQ  1  PQ  − 1  PP   PP  1
2
1
2
dn se ax sin bxd − r ne ax sinsbx 1 nd dx n where a and b are positive numbers, r 2 − a 2 1 b 2, and − tan21sbyad.
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18. Evaluate lim
xl
e sin x 2 1 . x2
19. Let T and N be the tangent and normal lines to the ellipse x 2y9 1 y 2y4 − 1 at any point P on the ellipse in the first quadrant. Let x T and yT be the x and yintercepts of T and x N and yN be the intercepts of N. As P moves along the ellipse in the first quadrant (but not on the axes), what values can x T , yT , x N, and yN take on? First try to guess the answers just by looking at the figure. Then use calculus to solve the problem and see how good your intuition is. y
yT
T
2
P
xN
0
N
yN
20. Evaluate lim
xl0
xT
x
3
sins3 1 xd2 2 sin 9 . x
21. (a) Use the identity for tansx 2 yd (see Equation 15b in Appendix D) to show that if two lines L 1 and L 2 intersect at an angle , then tan −
m 2 2 m1 1 1 m1 m 2
where m1 and m 2 are the slopes of L 1 and L 2, respectively. (b) The angle between the curves C1 and C2 at a point of intersection P is defined to be the angle between the tangent lines to C1 and C2 at P (if these tangent lines exist). Use part (a) to find, correct to the nearest degree, the angle between each pair of curves at each point of intersection. (i) y − x 2 and y − sx 2 2d2 (ii) x 2 2 y 2 − 3 and x 2 2 4x 1 y 2 1 3 − 0 22. Let Psx 1, y1d be a point on the parabola y 2 − 4px with focus Fs p, 0d. Let be the angle between the parabola and the line segment FP, and let be the angle between the horizontal line y − y1 and the parabola as in the figure. Prove that − . (Thus, by a principle of geometrical optics, light from a source placed at F will be reflected along a line parallel to the xaxis. This explains why paraboloids, the surfaces obtained by rotating parabolas about their axes, are used as the shape of some automobile headlights and mirrors for telescopes.) y
0
å
∫ P(⁄, ›)
y=› x
F( p, 0) ¥=4px
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Q ¨ A
R
P
¨ O
23. Suppose that we replace the parabolic mirror of Problem 22 by a spherical mirror. Although the mirror has no focus, we can show the existence of an approximate focus. In the figure, C is a semicircle with center O. A ray of light coming in toward the mirror parallel to the axis along the line PQ will be reflected to the point R on the axis so that /PQO − /OQR (the angle of incidence is equal to the angle of reflection). What happens to the point R as P is taken closer and closer to the axis? 24. If f and t are differentiable functions with f s0d − ts0d − 0 and t9s0d ± 0, show that
C
lim
xl0
FIGURE FOR PROBLEM 23
25. Evaluate lim
xl0
f sxd f 9s0d − tsxd t9s0d
sinsa 1 2xd 2 2 sinsa 1 xd 1 sin a . x2
26. (a) The cubic function f sxd − xsx 2 2dsx 2 6d has three distinct zeros: 0, 2, and 6. Graph f and its tangent lines at the average of each pair of zeros. What do you notice? (b) Suppose the cubic function f sxd − sx 2 adsx 2 bdsx 2 cd has three distinct zeros: a, b, and c. Prove, with the help of a computer algebra system, that a tangent line drawn at the average of the zeros a and b intersects the graph of f at the third zero. 27. For what value of k does the equation e 2x − ksx have exactly one solution? 28. For which positive numbers a is it true that a x > 1 1 x for all x ? 29. If y−
show that y9 −
x sa 2 2 1
2
2 sa 2 2 1
arctan
sin x a 1 sa 2 2 1 1 cos x
1 . a 1 cos x
30. G iven an ellipse x 2ya 2 1 y 2yb 2 − 1, where a ± b, find the equation of the set of all points from which there are two tangents to the curve whose slopes are (a) reciprocals and (b) negative reciprocals. 31. Find the two points on the curve y − x 4 2 2x 2 2 x that have a common tangent line. 32. Suppose that three points on the parabola y − x 2 have the property that their normal lines intersect at a common point. Show that the sum of their xcoordinates is 0. 33. A lattice point in the plane is a point with integer coordinates. Suppose that circles with radius r are drawn using all lattice points as centers. Find the smallest value of r such that any line with slope 25 intersects some of these circles. 34. A cone of radius r centimeters and height h centimeters is lowered point first at a rate of 1 cmys into a tall cylinder of radius R centimeters that is partially filled with water. How fast is the water level rising at the instant the cone is completely submerged? 35. A container in the shape of an inverted cone has height 16 cm and radius 5 cm at the top. It is partially filled with a liquid that oozes through the sides at a rate proportional to the area of the container that is in contact with the liquid. (The surface area of a cone is rl, where r is the radius and l is the slant height.) If we pour the liquid into the container at a rate of 2 cm3ymin, then the height of the liquid decreases at a rate of 0.3 cmymin when the height is 10 cm. If our goal is to keep the liquid at a constant height of 10 cm, at what rate should we pour the liquid into the container?
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The great mathematician Leonard Euler observed “… nothing at all takes place in the universe in which some rule of maximum or minimum does not appear.” In Exercise 4.7.53 you will use calculus to show that bees construct the cells in their hive in a shape that minimizes surface area. Kostiantyn Kravchenko / Shutterstock.com
4
Applications of Differentiation WE HAVE ALREADY INVESTIGATED SOME of the applications of derivatives, but now that we know the differentiation rules we are in a better position to pursue the applications of differentiation in greater depth. Here we learn what derivatives tell us about the shape of a graph of a function and, in particular, how they help us locate maximum and minimum values of functions. Many practical problems require us to minimize a cost or maximize an area or somehow find the best possible outcome of a situation. In particular, we will be able to investigate the optimal shape of a can and to explain the location of rainbows in the sky.
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280
CHAPTER 4 Applications of Differentiation
4.1 Maximum and Minimum Values Some of the most important applications of differential calculus are optimization problems, in which we are required to find the optimal (best) way of doing something. Here are examples of such problems that we will solve in this chapter: ● ●
● ●
What is the shape of a can that minimizes manufacturing costs? What is the maximum acceleration of a spacecraft? (This is an important question for the astronauts who have to withstand the effects of acceleration.) What is the radius of a contracted windpipe that expels air most rapidly during a cough? At what angle should blood vessels branch so as to minimize the energy expended by the heart in pumping blood?
These problems can be reduced to finding the maximum or minimum values of a function. Let’s first explain exactly what we mean by maximum and minimum values.
■ Absolute and Local Extreme Values
y
We see that the highest point on the graph of the function f shown in Figure 1 is the point s3, 5d. In other words, the largest value of f is f s3d − 5. Likewise, the smallest value is f s6d − 2. We say that f s3d − 5 is the absolute maximum of f and f s6d − 2 is the absolute minimum. In general, we use the following definition.
4 2 0
2
4
x
6
1 Definitio Let c be a number in the domain D of a function f. Then f scd is the ● absolute maximum value of f on D if f scd > f sxd for all x in D. ● absolute minimum value of f on D if f scd < f sxd for all x in D.
FIGURE 1 y
f(d) f(a) a
0
b
c
d
x
e
FIGURE 2 Abs min f sad, abs max f sd d, loc min f scd, f sed, loc max f sbd, f sd d y loc max
loc and abs min
I
J
K
4
8
12
6 4
loc min
2 0
FIGURE 3
x
An absolute maximum or minimum is sometimes called a global maximum or minimum. The maximum and minimum values of f are called extreme values of f. Figure 2 shows the graph of a function f with absolute maximum at d and absolute minimum at a. Note that sd, f sddd is the highest point on the graph and sa, f sadd is the lowest point. In Figure 2, if we consider only values of x near b [for instance, if we restrict our attention to the interval sa, cd], then f sbd is the largest of those values of f sxd and is called a local maximum value of f. Likewise, f scd is called a local minimum value of f because f scd < f sxd for x near c [in the interval sb, dd, for instance]. The function f also has a local minimum at e. In general, we have the following definition. 2 Definitio The number f scd is a ● local maximum value of f if f scd > f sxd when x is near c. ● local minimum value of f if f scd < f sxd when x is near c. In Definition 2 (and elsewhere), if we say that something is true near c, we mean that it is true on some open interval containing c. (Thus a local maximum or minimum can’t occur at an endpoint.) For instance, in Figure 3 we see that f s4d − 5 is a local minimum because it’s the smallest value of f on the interval I. It’s not the absolute minimum because f sxd takes on smaller values when x is near 12 (in the interval K, for instance). In fact f s12d − 3 is both a local minimum and the absolute minimum. Similarly, f s8d − 7 is a local maximum, but not the absolute maximum because f takes on larger values near 1.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
281
SECTION 4.1 Maximum and Minimum Values y
EXAMPLE 1 The graph of the function
(_1, 37)
y=3x$16˛+18≈
f sxd − 3x 4 2 16x 3 1 18x 2 21 < x < 4
(1, 5) _1
1
2
3
4
5
x
(3, _27)
is shown in Figure 4. You can see that f s1d − 5 is a local maximum, whereas the absolute maximum is f s21d − 37. (This absolute maximum is not a local maximum because it occurs at an endpoint.) Also, f s0d − 0 is a local minimum and f s3d − 227 is both a local and an absolute minimum. Note that f has neither a local nor an absolute maximum at x − 4. n
EXAMPLE 2 The function f sxd − cos x takes on its (local and absolute) maximum value of 1 infinitely many times, because cos 2n − 1 for any integer n and 21 < cos x < 1 for all x. (See Figure 5.) Likewise, coss2n 1 1d − 21 is its minimum value, where n is any integer.
FIGURE 4
y
Local and absolute maximum
0
FIGURE 5 y − cos x y
3π
Local and absolute minimum
x
n
f s0d − 0 is the absolute (and local) minimum value of f . This corresponds to the fact that the origin is the lowest point on the parabola y − x 2. (See Figure 6.) However, there is no highest point on the parabola and so this function has no maximum value. n
x
EXAMPLE 4 From the graph of the function f sxd − x 3, shown in Figure 7, we see that
FIGURE 6 Mimimum value 0, no maximum y
this function has neither an absolute maximum value nor an absolute minimum value. In fact, it has no local extreme values either. n We have seen that some functions have extreme values, whereas others do not. The following theorem gives conditions under which a function is guaranteed to possess extreme values.
y=˛ 0
2π
EXAMPLE 3 If f sxd − x 2, then f sxd > f s0d because x 2 > 0 for all x. Therefore
y=≈
0
π
x
3 The Extreme Value Theorem If f is continuous on a closed interval fa, bg, then f attains an absolute maximum value f scd and an absolute minimum value f sdd at some numbers c and d in fa, bg.
FIGURE 7 No mimimum, no maximum
The Extreme Value Theorem is illustrated in Figure 8. Note that an extreme value can be taken on more than once. Although the Extreme Value Theorem is intuitively very plausible, it is difficult to prove and so we omit the proof. y
y
y
FIGURE 8 Functions continuous on a closed interval always attain extreme values.
0
a
c
d b
x
0
a
c
d=b
x
0
a c¡
d
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
c™ b
x
282
CHAPTER 4 Applications of Differentiation
Figures 9 and 10 show that a function need not possess extreme values if either hypothesis (continuity or closed interval) is omitted from the Extreme Value Theorem. y
y
3
g f 1 0
FIGURE 9
1 2
x
This function has minimum value f(2)=0, but no maximum value.
0
2
x
FIGURE 10
This continuous function g has no maximum or minimum.
The function f whose graph is shown in Figure 9 is defined on the closed interval [0, 2] but has no maximum value. (Notice that the range of f is [0, 3d. The function takes on values arbitrarily close to 3, but never actually attains the value 3.) This does not contradict the Extreme Value Theorem because f is not continuous. [Nonetheless, a discontinuous function could have maximum and minimum values. See Exercise 13(b).] The function t shown in Figure 10 is continuous on the open interval s0, 2d but has neither a maximum nor a minimum value. [The range of t is s1, `d. The function takes on arbitrarily large values.] This does not contradict the Extreme Value Theorem because the interval s0, 2d is not closed.
■ Critical Numbers and the Closed Interval Method
y
The Extreme Value Theorem says that a continuous function on a closed interval has a maximum value and a minimum value, but it does not tell us how to find these extreme values. Notice in Figure 8 that the absolute maximum and minimum values that are between a and b occur at local maximum or minimum values, so we start by looking for local extreme values. Figure 11 shows the graph of a function f with a local maximum at c and a local minimum at d. It appears that at the maximum and minimum points the tangent lines are horizontal and therefore each has slope 0. We know that the derivative is the slope of the tangent line, so it appears that f 9scd − 0 and f 9sdd − 0. The following theorem says that this is always true for differentiable functions.
{c, f(c)}
{d, f (d )} 0
c
FIGURE 11
d
x
4 Fermat’s Theorem If f has a local maximum or minimum at c, and if f 9scd exists, then f 9scd − 0. PROOF Suppose, for the sake of definiteness, that f has a local maximum at c. Then, according to Definition 2, f scd > f sxd if x is sufficiently close to c. This implies that if h is sufficiently close to 0, with h being positive or negative, then f scd > f sc 1 hd and therefore 5
f sc 1 hd 2 f scd < 0
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.1 Maximum and Minimum Values
Fermat Fermat’s Theorem is named after Pierre Fermat (1601–1665), a French lawyer who took up mathematics as a hobby. Despite his amateur status, Fermat was one of the two inventors of analytic geometry (Descartes was the other). His methods for finding tangents to curves and maximum and minimum values (before the invention of limits and derivatives) made him a forerunner of Newton in the creation of differential calculus.
283
We can divide both sides of an inequality by a positive number. Thus, if h . 0 and h is sufficiently small, we have f sc 1 hd 2 f scd 0 h So, taking the lefthand limit, we have f 9scd − lim
hl0
f sc 1 hd 2 f scd f sc 1 hd 2 f scd − lim2 >0 h l0 h h
We have shown that f 9scd > 0 and also that f 9scd < 0. Since both of these inequalities must be true, the only possibility is that f 9scd − 0. We have proved Fermat’s Theorem for the case of a local maximum. The case of a local minimum can be proved in a similar manner, or see Exercise 81 for an alternate method. ■ The following examples caution us against reading too much into Fermat’s Theorem: we can’t expect to locate extreme values simply by setting f 9sxd − 0 and solving for x.
y
y=˛
EXAMPLE 5 If f sxd − x 3, then f 9sxd − 3x 2, so f 9s0d − 0. But f has no maximum or
0
x
FIGURE 12
If f sxd − x 3, then f 9s0d − 0, but f has no maximum or minimum. y
y= x 0
FIGURE 13
 
x
If f sxd − x , then f s0d − 0 is a minimum value, but f 9s0d does not exist.
minimum at 0, as you can see from its graph in Figure 12. (Or observe that x 3 . 0 for x . 0 but x 3 , 0 for x , 0.) The fact that f 9s0d − 0 simply means that the curve y − x 3 has a horizontal tangent at s0, 0d. Instead of having a maximum or minimum at s0, 0d, the curve crosses its horizontal tangent there. n
 
EXAMPLE 6 The function f sxd − x has its (local and absolute) minimum value at 0, but that value can’t be found by setting f 9sxd − 0 because, as was shown in Example 2.8.5, f 9s0d does not exist. (See Figure 13.)
n
WARNING Examples 5 and 6 show that we must be careful when using Fermat’s Theorem. Example 5 demonstrates that even when f 9scd − 0 there need not be a maximum or minimum at c. (In other words, the converse of Fermat’s Theorem is false in general.) Furthermore, there may be an extreme value even when f 9scd does not exist (as in Example 6). Fermat’s Theorem does suggest that we should at least start looking for extreme values of f at the numbers c where f 9scd − 0 or where f 9scd does not exist. Such numbers are given a special name.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
284
CHAPTER 4 Applications of Differentiation
6 Definitio A critical number of a function f is a number c in the domain of f such that either f 9scd − 0 or f 9scd does not exist.
EXAMPLE 7 Find the critical numbers of (a) f sxd − x 3 2 3x 2 1 1 and
(b) f sxd − x 3y5s4 2 xd.
SOLUTION (a) The derivative of f is f 9sxd − 3x 2 2 6x − 3xsx 2 2d. Since f 9sxd exists for all x, the only critical numbers of f occur when f 9sxd − 0, that is, when x − 0 or x − 2. (b) First note that the domain of f is R. The Product Rule gives
Figure 14 shows a graph of the function f in Example 7(b). It supports our answer because there is a horizontal tangent when x − 1.5 fwhere f 9sxd − 0g and a vertical tangent when x − 0 fwhere f 9sxd is undefinedg.
f 9sxd − x 3y5s21d 1 s4 2 xd(53 x22y5) − 2x 3y5 1 −
3.5
3s4 2 xd 5x 2 y5
25x 1 3s4 2 xd 12 2 8x − 2y5 5x 5x 2y5
[The same result could be obtained by first writing f sxd − 4x 3y5 2 x 8y5.] Therefore f 9sxd − 0 if 12 2 8x − 0, that is, x − 32, and f 9sxd does not exist when x − 0. Thus the critical numbers are 32 and 0. n 5
_0.5
In terms of critical numbers, Fermat’s Theorem can be rephrased as follows (compare Definition 6 with Theorem 4):
_2
FIGURE 14
7 If f has a local maximum or minimum at c, then c is a critical number of f. To find an absolute maximum or minimum of a continuous function on a closed interval, we note that either it is local [in which case it occurs at a critical number by (7)] or it occurs at an endpoint of the interval, as we see from the examples in Figure 8. Thus the following threestep procedure always works. The Closed Interval Method To find the absolute maximum and minimum values of a continuous function f on a closed interval fa, bg: 1. Find the values of f at the critical numbers of f in sa, bd. 2. Find the values of f at the endpoints of the interval. 3. The largest of the values from Steps 1 and 2 is the absolute maximum value; the smallest of these values is the absolute minimum value.
EXAMPLE 8 Find the absolute maximum and minimum values of the function f sxd − x 3 2 3x 2 1 1 212 < x < 4
f
g
SOLUTION Since f is continuous on 212, 4 , we can use the Closed Interval Method. In Example 7(a) we found the critical numbers x − 0 and x − 2. Notice that each of these critical numbers lies in the interval (212 , 4). The values of f at these critical numbers are f s0d − 1 f s2d − 23 The values of f at the endpoints of the interval are f (212 ) − 18 f s4d − 17 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.1 Maximum and Minimum Values y 20
y=˛3≈+1 (4, 17)
15 10 5 _1 0 _5
1
3
x
4
EXAMPLE 9 (a) Use a calculator or computer to estimate the absolute minimum and maximum values of the function f sxd − x 2 2 sin x, 0 < x < 2. (b) Use calculus to find the exact minimum and maximum values.
FIGURE 15
8
0 _1
Comparing these four numbers, we see that the absolute maximum value is f s4d − 17 and the absolute minimum value is f s2d − 23. In this example the absolute maximum occurs at an endpoint, whereas the absolute minimum occurs at a critical number. The graph of f is sketched in Figure 15. n With graphing software or a graphing calculator it is possible to estimate maximum and minimum values very easily. But, as the next example shows, calculus is needed to find the exact values.
2 (2, _3)
285
2π
SOLUTION (a) Figure 16 shows a graph of f in the viewing rectangle f0, 2g by f21, 8g. The absolute maximum value is about 6.97 and it occurs when x < 5.24. Similarly, the absolute minimum value is about 20.68 and it occurs when x < 1.05. It is possible to get more accurate numerical estimates, but for exact values we must use calculus. (b) The function f sxd − x 2 2 sin x is continuous on f0, 2g. Since f 9sxd − 1 2 2 cos x, we have f 9sxd − 0 when cos x − 12 and this occurs when x − y3 or 5y3. The values of f at these critical numbers are
FIGURE 16
f sy3d − and
f s5y3d −
2 2 sin − 2 s3 < 20.684853 3 3 3 5 5 5 2 2 sin − 1 s3 < 6.968039 3 3 3
The values of f at the endpoints are f s0d − 0 f s2d − 2 < 6.28 Comparing these four numbers and using the Closed Interval Method, we see that the absolute minimum value is f sy3d − y3 2 s3 and the absolute maximum value is f s5y3d − 5y3 1 s3 . The values from part (a) serve as a check on our work. n
EXAMPLE 10 The Hubble Space Telescope was deployed on April 24, 1990, by the space shuttle Discovery. A model for the velocity of the shuttle during this mission, from liftoff at t − 0 until the solid rocket boosters were jettisoned at t − 126 seconds, is given by vstd − 0.000397t 3 2 0.02752t 2 1 7.196t 2 0.9397
NASA
(in meters per second). Using this model, estimate the absolute maximum and minimum values of the acceleration of the shuttle between liftoff and the jettisoning of the boosters. SOLUTION We are asked for the extreme values not of the given velocity function, but rather of the acceleration function. So we first need to differentiate to find the acceleration: astd − v9std −
d s0.000397t 3 2 0.02752t 2 1 7.196t 2 0.9397d dt
− 0.001191t 2 2 0.05504t 1 7.196 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
286
CHAPTER 4 Applications of Differentiation
We now apply the Closed Interval Method to the continuous function a on the interval 0 < t < 126. Its derivative is a9std − 0.0023808t 2 0.05504 The only critical number occurs when a9std − 0: t1 −
0.05504 < 23.12 0.0023808
Evaluating astd at the critical number and at the endpoints, we have as0d − 7.196 ast1 d 5 as23.12d 5 6.56 as126d < 19.16 So the maximum acceleration is about 19.16 mys2 and the minimum acceleration is about 6.56 mys2.
n
4.1 Exercises 1. Explain the difference between an absolute minimum and a local minimum. 2. Suppose f is a continuous function defined on a closed interval fa, bg. (a) What theorem guarantees the existence of an absolute maximum value and an absolute minimum value for f ? (b) What steps would you take to find those maximum and minimum values? 3–4 For each of the numbers a, b, c, d, r, and s, state whether the function whose graph is shown has an absolute maximum or minimum, a local maximum or minimum, or neither a maximum nor a minimum. 3. y
5–6 Use the graph to state the absolute and local maximum and minimum values of the function. 5. y
6.
y
y=©
y=ƒ
1 0
1
1 x
0
1
x
7–10 Sketch the graph of a function f that is continuous on [1, 5] and has the given properties. 7. Absolute maximum at 5, absolute minimum at 2, local maximum at 3, local minima at 2 and 4 8. Absolute maximum at 4, absolute minimum at 5, local maximum at 2, local minimum at 3
0 a
b
c
d
r
s
x
10. A bsolute maximum at 2, absolute minimum at 5, 4 is a critical number but there is no local maximum or minimum there.
4. y
0
9. Absolute minimum at 3, absolute maximum at 4, local maximum at 2
a
b
c
d
r
s
x
11. (a) Sketch the graph of a function that has a local maximum at 2 and is differentiable at 2. (b) Sketch the graph of a function that has a local maximum at 2 and is continuous but not differentiable at 2. (c) Sketch the graph of a function that has a local maximum at 2 and is not continuous at 2.
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SECTION 4.1 Maximum and Minimum Values
12. (a) Sketch the graph of a function on [21, 2] that has an absolute maximum but no local maximum. (b) Sketch the graph of a function on [21, 2] that has a local maximum but no absolute maximum. 13. (a) Sketch the graph of a function on [21, 2] that has an absolute maximum but no absolute minimum. (b) Sketch the graph of a function on [21, 2] that is discontinuous but has both an absolute maximum and an absolute minimum. 14. (a) Sketch the graph of a function that has two local maxima, one local minimum, and no absolute minimum. (b) Sketch the graph of a function that has three local minima, two local maxima, and seven critical numbers. 15–28 Sketch the graph of f by hand and use your sketch to find the absolute and local maximum and minimum values of f. (Use the graphs and transformations of Sections 1.2 and 1.3.)
45. f sd − 2 cos 1 sin2
46. pstd − te 4t
47. tsxd − x 2 ln x
48. Bsud − 4 tan21u 2 u
; 49–50 A formula for the derivative of a function f is given. How many critical numbers does f have? 49. f 9sxd − 5e20.1  x  sin x 2 1
50. f 9sxd −
51. f sxd − 12 1 4x 2 x 2, f0, 5g 52. f sxd − 5 1 54x 2 2x 3, f0, 4g 53. f sxd − 2x 3 2 3x 2 2 12x 1 1, f22, 3g 54. f sxd − x 3 2 6x 2 1 5, f23, 5g 55. f sxd − 3x 4 2 4x 3 2 12x 2 1 1, f22, 3g
16. f sxd − x , 21 < x , 2
56. f std − st 2 2 4d 3, f22, 3g
17. f sxd − 1yx, x > 1
1 , f0.2, 4g x x 58. f sxd − 2 , f0, 3g x 2x11 57. f sxd − x 1
18. f sxd − 1yx, 1 , x , 3 19. f sxd − sin x, 0 < x , y2 20. f sxd − sin x, 0 , x < y2
3 59. f std − t 2 s t , f21, 4g
21. f sxd − sin x, 2y2 < x < y2
60. f sxd −
22. f std − cos t, 23y2 < t < 3y2 24. f sxd − x
25. f sxd − 1 2 sx
26. f sxd − e x
62. f sd − 1 1 cos2 , [y4, ]
f g
63. f sxd − x22 ln x, 12 , 4
x2 if 21 < x < 0 27. f sxd − 2 2 3x if 0 , x < 1
64. f sxd − xe , f23, 1g xy2
65. f sxd − lnsx 2 1 x 1 1d, f21, 1g
2x 1 1 if 0 < x , 1 28. f sxd − 4 2 2x if 1 < x < 3
66. f sxd − x 2 2 tan21 x, f0, 4g
29–48 Find the critical numbers of the function. 29. f sxd − 3x 1 x 2 2
30. tsvd − v 2 12v 1 4
31. f sxd − 3x 4 1 8x 3 2 48x 2
32. f sxd − 2x 3 1 x 2 1 8x
33. tstd − t 5 1 5t 3 1 50t
34. Asxd − 3 2 2x
2
ex , [0, 3] 1 1 x2
61. f std − 2 cos t 1 sin 2t, f0, y2g
 
23. f sxd − ln x, 0 , x < 2
H H
100 cos 2 x 21 10 1 x 2
51–66 Find the absolute maximum and absolute minimum values of f on the given interval.
15. f sxd − 3 2 2x, x > 21 2
287
3

35. tsyd −
y21 y2 2 y 1 1
36. hs pd −
p21 p2 1 4
37. psxd −
x2 1 2 2x 2 1
38. qstd −
t2 1 9 t2 2 9

39. hstd − t 3y4 2 2 t 1y4
3 40. tsxd − s 4 2 x2
41. Fsxd − x 4y5sx 2 4d 2
42. hsxd − x21y3sx 2 2d
43. f sxd − x 1y3s4 2 xd2y3
44. f sd − 1 s2 cos
67. I f a and b are positive numbers, find the maximum value of f sxd − x as1 2 xd b, 0 < x < 1. se a graph to estimate the critical numbers of ; 68. U f sxd − 1 1 5x 2 x 3 correct to one decimal place.


; 69–72 (a) Use a graph to estimate the absolute maximum and minimum values of the function to two decimal places. (b) Use calculus to find the exact maximum and minimum values. 69. f sxd − x 5 2 x 3 1 2, 21 < x < 1 70. f sxd − e x 1 e 22x, 0 < x < 1 71. f sxd − x sx 2 x 2 72. f sxd − x 2 2 cos x, 22 < x < 0
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
288
CHAPTER 4 Applications of Differentiation
73. A fter an alcoholic beverage is consumed, the concentration of alcohol in the bloodstream (blood alcohol concentration, or BAC) surges as the alcohol is absorbed, followed by a gradual decline as the alcohol is metabolized. The function
Event
Cstd − 0.135te22.802t
Source: Adapted from P. Wilkinson et al., “Pharmacokinetics of Ethanol after Oral Administration in the Fasting State,” Journal of Pharmacokinetics and Biopharmaceutics 5 (1977): 207–24.
Cstd − 8se20.4t 2 e20.6t d where the time t is measured in hours and C is measured in mgymL. What is the maximum concentration of the antibiotic during the first 12 hours? 75. B etween 0°C and 30°C, the volume V (in cubic centimeters) of 1 kg of water at a temperature T is given approximately by the formula V − 999.87 2 0.06426T 1 0.0085043T 2 2 0.0000679T 3 Find the temperature at which water has its maximum density.
W sin 1 cos
where is a positive constant called the coefficient of friction and where 0 < < y2. Show that F is minimized when tan − . 77. T he water level, measured in meters above mean sea level, of Lake Lanier in Georgia, USA, during 2012 can be modeled by the function Lstd − 0.00439t 3 2 0.1273t 2 1 0.8239t 1 323.1 where t is measured in months since January 1, 2012. Estimate when the water level was highest during 2012. 78. In 1992 the space shuttle Endeavour was launched on mission STS49 in order to install a new perigee kick motor in an Intelsat communications satellite. The table gives the velocity data for the shuttle between liftoff and the jettisoning of the solid rocket boosters. (a) Use a graphing calculator or computer to find the cubic polynomial that best models the velocity of the shuttle for the time interval t [ f0, 125g. Then graph this polynomial.
0 10 15 20 32 59 62 125
0 56.4 97.2 136.2 226.2 403.9 440.4 1265.2
79. W hen a foreign object lodged in the trachea forces a person to cough, the diaphragm thrusts upward, causing an increase in pressure in the lungs. This is accompanied by a contraction of the trachea, making a narrower channel for the expelled air to flow through. For a given amount of air to escape in a fixed time, it must move faster through the narrower channel than the wider one. The greater the velocity of the airstream, the greater the force on the foreign object. Xrays show that the radius of the circular tracheal tube contracts to about twothirds of its normal radius during a cough. According to a mathematical model of coughing, the velocity v of the airstream is related to the radius r of the trachea by the equation vsrd − ksr0 2 rdr 2 12 r0 < r < r0
76. A n object with weight W is dragged along a horizontal plane by a force acting along a rope attached to the object. If the rope makes an angle with the plane, then the magnitude of the force is F−
Time (s) Velocity (mys)
Launch Begin roll maneuver End roll maneuver Throttle to 89% Throttle to 67% Throttle to 104% Maximum dynamic pressure Solid rocket booster separation
models the average BAC, measured in gydL, of a group of eight male subjects t hours after rapid consumption of 15 mL of ethanol (corresponding to one alcoholic drink). What is the maximum average BAC during the first 3 hours? When does it occur?
74. A fter an antibiotic tablet is taken, the concentration of the antibiotic in the bloodstream is modeled by the function
(b) Find a model for the acceleration of the shuttle and use it to estimate the maximum and minimum values of the acceleration during the first 125 seconds.
where k is a constant and r0 is the normal radius of the trachea. The restriction on r is due to the fact that the tracheal wall stiffens under pressure and a contraction greater than 1 2 r0 is prevented (otherwise the person would suffocate).
f
g
(a) Determine the value of r in the interval 12 r 0 , r 0 at which v has an absolute maximum. How does this compare with experimental evidence? (b) What is the absolute maximum value of v on the interval? (c) Sketch the graph of v on the interval f0, r0 g.
80. Prove that the function f sxd − x 101 1 x 51 1 x 1 1 has neither a local maximum nor a local minimum. 81. (a) If f has a local minimum value at c, show that the function tsxd − 2f sxd has a local maximum value at c. (b) Use part (a) to prove Fermat’s Theorem for the case in which f has a local minimum at c. 82. A cubic function is a polynomial of degree 3; that is, it has the form f sxd − ax 3 1 bx 2 1 cx 1 d, where a ± 0. (a) Show that a cubic function can have two, one, or no critical number(s). Give examples and sketches to illustrate the three possibilities. (b) How many local extreme values can a cubic function have?
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
APPLIED PROJECT The Calculus of Rainbows
289
APPLIED PROJECT THE CALCULUS OF RAINBOWS Rainbows are created when raindrops scatter sunlight. They have fascinated mankind since ancient times and have inspired attempts at scientific explanation since the time of Aristotle. In this project we use the ideas of Descartes and Newton to explain the shape, location, and colors of rainbows. å A from sun
∫
∫
O
B
D(å )
∫
∫
C
å to observer
Formation of the primary rainbow
1. The figure shows a ray of sunlight entering a spherical raindrop at A. Some of the light is reflected, but the line AB shows the path of the part that enters the drop. Notice that the light is refracted toward the normal line AO and in fact Snell’s Law says that sin − k sin , where is the angle of incidence, is the angle of refraction, and k < 43 is the index of refraction for water. At B some of the light passes through the drop and is refracted into the air, but the line BC shows the part that is reflected. (The angle of incidence equals the angle of reflection.) When the ray reaches C, part of it is reflected, but for the time being we are more interested in the part that leaves the raindrop at C. (Notice that it is refracted away from the normal line.) The angle of deviation Dsd is the amount of clockwise rotation that the ray has undergone during this threestage process. Thus Dsd − s 2 d 1 s 2 2d 1 s 2 d − 1 2 2 4 how that the minimum value of the deviation is Dsd < 1388 and occurs when S < 59.48.
rays from sun
The significance of the minimum deviation is that when < 59.48 we have D9sd < 0, so DDyD < 0. This means that many rays with < 59.48 become deviated by approximately the same amount. It is the concentration of rays coming from near the direction of minimum deviation that creates the brightness of the primary rainbow. The figure at the left shows that the angle of elevation from the observer up to the highest point on the rainbow is 180 8 2 1388 − 428. (This angle is called the rainbow angle.)
138° rays from sun
42°
2. Problem 1 explains the location of the primary rainbow, but how do we explain the colors? Sunlight comprises a range of wavelengths, from the red range through orange, yellow, green, blue, indigo, and violet. As Newton discovered in his prism experiments of 1666, the index of refraction is different for each color. (The effect is called dispersion.) For red light the refractive index is k < 1.3318, whereas for violet light it is k < 1.3435. By repeating the calculation of Problem 1 for these values of k, show that the rainbow angle is about 42.38 for the red bow and 40.68 for the violet bow. So the rainbow really consists of seven individual bows corresponding to the seven colors.
observer
C
to observer from sun
å
∫
D
∫
å
∫
3. Perhaps you have seen a fainter secondary rainbow above the primary bow. That results from the part of a ray that enters a raindrop and is refracted at A, reflected twice (at B and C), and refracted as it leaves the drop at D (see the figure at the left). This time the deviation angle Dsd is the total amount of counterclockwise rotation that the ray undergoes in this fourstage process. Show that
∫
∫
∫
A
Formation of the secondary rainbow
Dsd − 2 2 6 1 2 B
and Dsad has a minimum value when cos −
Î
k2 2 1 8
(continued )
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
290
CHAPTER 4 Applications of Differentiation
Taking k − 43, show that the minimum deviation is about 1298 and so the rainbow angle for the secondary rainbow is about 518, as shown in the figure at the left.
Leonid Andronov / Shutterstock.com
4. Show that the colors in the secondary rainbow appear in the opposite order from those in the primary rainbow.
42° 51°
4.2 The Mean Value Theorem We will see that many of the results of this chapter depend on one central fact, which is called the Mean Value Theorem.
■ Rolle’s Theorem To arrive at the Mean Value Theorem, we first need the following result. Rolle
Rolle’s Theorem Let f be a function that satisfies the following three hypotheses: 1. f is continuous on the closed interval fa, bg. 2. f is differentiable on the open interval sa, bd. 3. f sad − f sbd
Rolle’s Theorem was first published i 1691 by the French mathematician Michel Rolle (1652–1719) in a book entitled Méthode pour resoudre les egalitez. He was a vocal critic of the methods of his day and attacked calculus as being a “collection of ingenious fallacies.” Later, however, he became convinced of the essential correctness of the methods of calculus.
y
0
Then there is a number c in sa, bd such that f 9scd − 0. Before giving the proof let’s take a look at the graphs of some typical functions that satisfy the three hypotheses. Figure 1 shows the graphs of four such functions. In each case it appears that there is at least one point sc, f scdd on the graph where the tangent is horizontal and therefore f 9scd − 0. Thus Rolle’s Theorem is plausible. y
a
c¡
(a)
c™ b
x
0
y
a
c
(b)
b
x
0
y
a
c¡
(c)
c™
b
x
0
a
c
b
x
(d)
FIGURE 1 Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.2 The Mean Value Theorem
291
PROOF There are three cases: PS
CASE I f sxd − k, a constant
Take cases
Then f 9sxd − 0, so the number c can be taken to be any number in sa, bd. CASE II f sxd . f sad for some x in sa, bd [as in Figure 1(b) or (c)] By the Extreme Value Theorem (which we can apply by hypothesis 1), f has a maximum value somewhere in fa, bg. Since f sad − f sbd, it must attain this maximum value at a number c in the open interval sa, bd. Then f has a local maximum at c and, by hypothesis 2, f is differentiable at c. Therefore f 9scd − 0 by Fermat’s Theorem. CASE III f sxd , f sad for some x in sa, bd [as in Figure 1(c) or (d)] By the Extreme Value Theorem, f has a minimum value in fa, bg and, since f sad − f sbd, it attains this minimum value at a number c in sa, bd. Again f 9scd − 0 by Fermat’s Theorem. ■
EXAMPLE 1 Let’s apply Rolle’s Theorem to the position function s − f std of a moving object. If the object is in the same place at two different instants t − a and t − b, then f sad − f sbd. Rolle’s Theorem says that there is some instant of time t − c between a and b when f 9scd − 0; that is, the velocity is 0. (In particular, you can see that this is true when a ball is thrown directly upward.) n Figure 2 shows a graph of the function f sxd − x 3 1 x 2 1 discussed in Example 2. Rolle’s Theorem shows that, no matter how much we enlarge the viewing rectangle, we can never find a second xintercept. 3
_2
2
EXAMPLE 2 Prove that the equation x 3 1 x 2 1 − 0 has exactly one real solution. SOLUTION First we use the Intermediate Value Theorem (2.5.10) to show that a solution exists. Let f sxd − x 3 1 x 2 1. Then f s0d − 21 , 0 and f s1d − 1 . 0. Since f is a polynomial, it is continuous, so the Intermediate Value Theorem states that there is a number c between 0 and 1 such that f scd − 0. Thus the given equation has a solution. To show that the equation has no other real solution, we use Rolle’s Theorem and argue by contradiction. Suppose that it had two solutions a and b. Then f sad − 0 − f sbd and, since f is a polynomial, it is differentiable on sa, bd and continuous on fa, bg. Thus, by Rolle’s Theorem, there is a number c between a and b such that f 9scd − 0. But f 9sxd − 3x 2 1 1 > 1 for all x
_3
FIGURE 2
(since x 2 > 0) so f 9sxd can never be 0. This gives a contradiction. Therefore the equation can’t have two real solutions.
n
■ The Mean Value Theorem Our main use of Rolle’s Theorem is in proving the following important theorem, which was first stated by another French mathematician, JosephLouis Lagrange.
The Mean Value Theorem is an example of what is called an existence theorem. Like the Intermediate Value Theorem, the Extreme Value Theorem, and Rolle’s Theorem, it guarantees that there exists a number with a certain property, but it doesn’t tell us how to find the number.
The Mean Value Theorem Let f be a function that satisfies the following hypotheses: 1. f is continuous on the closed interval fa, bg. 2. f is differentiable on the open interval sa, bd. Then there is a number c in sa, bd such that 1
f 9scd −
f sbd 2 f sad b2a
or, equivalently, 2
f sbd 2 f sad − f 9scdsb 2 ad
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
292
CHAPTER 4 Applications of Differentiation
Before proving this theorem, we can see that it is reasonable by interpreting it geomet rically. Figures 3 and 4 show the points Asa, f sadd and Bsb, f sbdd on the graphs of two differentiable functions. The slope of the secant line AB is 3
mAB −
f sbd 2 f sad b2a
which is the same expression as on the right side of Equation 1. Since f 9scd is the slope of the tangent line at the point sc, f scdd, the Mean Value Theorem, in the form given by Equa tion 1, says that there is at least one point Psc, f scdd on the graph where the slope of the tangent line is the same as the slope of the secant line AB. In other words, there is a point P where the tangent line is parallel to the secant line AB. (Imagine a line far away that stays parallel to AB while moving toward AB until it touches the graph for the first time.) y
y
P { c, f(c)}
P¡
B
P™
A
A{a, f(a)} B { b, f(b)} 0
a
c
b
x
0
FIGURE 3 y
h(x)
A ƒ
0
b
f(b)f(a) f(a)+ (xa) ba
FIGURE 5
x
c¡
c™
b
x
FIGURE 4
PROOF We apply Rolle’s Theorem to a new function h defined as the difference between f and the function whose graph is the secant line AB. Using Equation 3 and the pointslope equation of a line, we see that the equation of the line AB can be written as
B x
a
y=ƒ
a
or as
y 2 f sad −
f sbd 2 f sad sx 2 ad b2a
y − f sad 1
f sbd 2 f sad sx 2 ad b2a
So, as shown in Figure 5, 4
hsxd − f sxd 2 f sad 2
f sbd 2 f sad sx 2 ad b2a
First we must verify that h satisfies the three hypotheses of Rolle’s Theorem. 1. The function h is continuous on fa, bg because it is the sum of f and a firstdegree polynomial, both of which are continuous. 2. The function h is differentiable on sa, bd because both f and the firstdegree polynomial are differentiable. In fact, we can compute h9 directly from Equation 4: h9sxd − f 9sxd 2
f sbd 2 f sad b2a
(Note that f sad and f f sbd 2 f sadgysb 2 ad are constants.)
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SECTION 4.2 The Mean Value Theorem
Lagrange and the Mean Value Theorem
3.
The Mean Value Theorem was first ormulated by JosephLouis Lagrange (1736–1813), born in Italy of a French father and an Italian mother. He was a child prodigy and became a professor in Turin at the age of 19. Lagrange made great contributions to number theory, theory of functions, theory of equations, and analytical and celestial mechanics. In particular, he applied calculus to the analysis of the stability of the solar system. At the invitation of Frederick the Great, he succeeded Euler at the Berlin Academy and, when Frederick died, Lagrange accepted King Louis XVI’s invitation to Paris, where he was given apartments in the Louvre and became a professor at the Ecole Polytechnique. Despite all the trappings of luxury and fame, he was a kind and quiet man, living only for science.
y
y=˛x
f sbd 2 f sad sa 2 ad − 0 b2a
hsbd − f sbd 2 f sad 2
f sbd 2 f sad sb 2 ad b2a
− f sbd 2 f sad 2 f f sbd 2 f sadg − 0 Therefore hsad − hsbd. Since h satisfies all the hypotheses of Rolle’s Theorem, that theorem says there is a number c in sa, bd such that h9scd − 0. Therefore 0 − h9scd − f 9scd 2 and so
f 9scd −
f sbd 2 f sad b2a
f sbd 2 f sad b2a
■
EXAMPLE 3 To illustrate the Mean Value Theorem with a specific function, let’s consider f sxd − x 3 2 x, a − 0, b − 2. Since f is a polynomial, it is continuous and differentiable for all x, so it is certainly continuous on f0, 2g and differentiable on s0, 2d. Therefore, by the Mean Value Theorem, there is a number c in s0, 2d such that f s2d 2 f s0d − f 9scds2 2 0d
B
Now f s2d − 6, f s0d − 0, and f 9sxd − 3x 2 2 1, so the above equation becomes 6 − s3c 2 2 1d2 − 6c 2 2 2
O c
FIGURE 6
hsad − f sad 2 f sad 2
293
2
x
which gives c 2 − 43 , that is, c − 62ys3. But c must lie in s0, 2d, so c − 2ys3. Figure 6 illustrates this calculation: the tangent line at this value of c is parallel to the secant line OB. n
EXAMPLE 4 If an object moves in a straight line with position function s − f std, then the average velocity between t − a and t − b is f sbd 2 f sad b2a and the velocity at t − c is f 9scd. Thus the Mean Value Theorem (in the form of Equation 1) tells us that at some time t − c between a and b the instantaneous velocity f 9scd is equal to that average velocity. For instance, if a car traveled 180 km in 2 hours, then the speedometer must have read 90 kmyh at least once. In general, the Mean Value Theorem can be interpreted as saying that there is a number at which the instantaneous rate of change is equal to the average rate of change over an interval. n The main significance of the Mean Value Theorem is that it enables us to obtain information about a function from information about its derivative. The next example provides an instance of this principle.
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294
CHAPTER 4 Applications of Differentiation
EXAMPLE 5 Suppose that f s0d − 23 and f 9sxd < 5 for all values of x. How large can f s2d possibly be?
SOLUTION We are given that f is differentiable (and therefore continuous) everywhere. In particular, we can apply the Mean Value Theorem on the interval f0, 2g. There exists a number c such that f s2d 2 f s0d − f 9scds2 2 0d f s2d − f s0d 1 2f 9scd − 23 1 2f 9scd
so
We are given that f 9sxd < 5 for all x, so in particular we know that f 9scd < 5. Multiplying both sides of this inequality by 2, we have 2f 9scd < 10, so f s2d − 23 1 2f 9scd < 23 1 10 − 7 The largest possible value for f s2d is 7.
n
The Mean Value Theorem can be used to establish some of the basic facts of differential calculus. One of these basic facts is the following theorem. Others will be discussed in the following sections. 5 Theorem If f 9sxd − 0 for all x in an interval sa, bd, then f is constant on sa, bd. PROOF Let x 1 and x 2 be any two numbers in sa, bd with x 1 , x 2 . Since f is differentiable on sa, bd, it must be differentiable on sx 1, x 2 d and continuous on fx 1, x 2 g. By applying the Mean Value Theorem to f on the interval fx 1, x 2 g, we get a number c such that x 1 , c , x 2 and f sx 2 d 2 f sx 1d − f 9scdsx 2 2 x 1d
6
Since f 9sxd − 0 for all x, we have f 9scd − 0, and so Equation 6 becomes f sx 2 d 2 f sx 1 d − 0 or f sx 2 d − f sx 1 d Therefore f has the same value at any two numbers x 1 and x 2 in sa, bd. This means that f is constant on sa, bd. ■ Corollary 7 says that if two functions have the same derivatives on an interval, then their graphs must be vertical translations of each other there. In other words, the graphs have the same shape, but they could be shifted up or down.
7 Corollary If f 9sxd − t9sxd for all x in an interval sa, bd, then f 2 t is constant on sa, bd; that is, f sxd − tsxd 1 c where c is a constant. PROOF Let Fsxd − f sxd 2 tsxd. Then F9sxd − f 9sxd 2 t9sxd − 0 for all x in sa, bd. Thus, by Theorem 5, F is constant; that is, f 2 t is constant.
■
NOTE Care must be taken in applying Theorem 5. Let
f sxd −
H
x 1 if x . 0 − x 21 if x , 0
 

The domain of f is D − hx x ± 0j and f 9sxd − 0 for all x in D. But f is obviously not a constant function. This does not contradict Theorem 5 because D is not an interval.
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295
SECTION 4.2 The Mean Value Theorem
EXAMPLE 6 Prove the identity tan21 x 1 cot21 x − y2. SOLUTION Although calculus isn’t needed to prove this identity, the proof using calculus is quite simple. If f sxd − tan21 x 1 cot21 x, then f 9sxd −
1 1 2 −0 1 1 x2 1 1 x2
for all values of x. Therefore f sxd − C, a constant. To determine the value of C, we put x − 1 [because we can evaluate f s1d exactly]. Then C − f s1d − tan21 1 1 cot21 1 − 1 − 4 4 2 Thus tan21 x 1 cot21 x − y2. n
4.2 Exercises 1. The graph of a function f is shown. Verify that f satisfies the hypotheses of Rolle’s Theorem on the interval f0, 8g. Then estimate the value(s) of c that satisfy the conclusion of Rolle’s Theorem on that interval.
5–8 The graph of a function f is shown. Does f satisfy the hypotheses of the Mean Value Theorem on the interval f0, 5g? If so, find a value c that satisfies the conclusion of the Mean Value Theorem on that interval. 5. y
y
6.
1 1 0
y
y=ƒ
0 x
1
2. Draw the graph of a function defined on f0, 8g such that f s0d − f s8d − 3 and the function does not satisfy the conclusion of Rolle’s Theorem on f0, 8g. 3. The graph of a function t is shown.
1 x
1
7. y
0
8.
1 0
1
x
y
1 x
1
0
1
x
y y=©
9–12 Verify that the function satisfies the three hypotheses of Rolle’s Theorem on the given interval. Then find all numbers c that satisfy the conclusion of Rolle’s Theorem.
1 0
9. f sxd − 2 x 2 2 4 x 1 5, f21, 3g 1
x
(a) Verify that t satisfies the hypotheses of the Mean Value Theorem on the interval f0, 8g. (b) Estimate the value(s) of c that satisfy the conclusion of the Mean Value Theorem on the interval f0, 8g. (c) Estimate the value(s) of c that satisfy the conclusion of the Mean Value Theorem on the interval f2, 6g.
4. Draw the graph of a function that is continuous on f0, 8g where f s0d − 1 and f s8d − 4 and that does not satisfy the conclusion of the Mean Value Theorem on f0, 8g.
10. f sxd − x 3 2 2x 2 2 4x 1 2, f22, 2g 11. f sxd − sins xy2d, fy2, 3y2g
f
g
12. f sxd − x 1 1y x, 12 , 2
13. Let f sxd − 1 2 x 2y3. Show that f s21d − f s1d but there is no number c in s21, 1d such that f 9scd − 0. Why does this not contradict Rolle’s Theorem? 14. Let f sxd − tan x. Show that f s0d − f sd but there is no number c in s0, d such that f 9scd − 0. Why does this not contradict Rolle’s Theorem?
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CHAPTER 4 Applications of Differentiation
15–18 Verify that the function satisfies the hypotheses of the Mean Value Theorem on the given interval. Then find all numbers c that satisfy the conclusion of the Mean Value Theorem. 15. f sxd − 2x 2 2 3x 1 1, f0, 2g 16. f sxd − x 3 2 3x 1 2, f22, 2g 17. f sxd − ln x, f1, 4g
18. f sxd − 1yx, f1, 3g
30. Suppose that 3 < f 9sxd < 5 for all values of x. Show that 18 < f s8d 2 f s2d < 30. 31. D oes there exist a function f such that f s0d − 21, f s2d − 4, and f 9sxd < 2 for all x ? 32. Suppose that f and t are continuous on fa, bg and differentiable on sa, bd. Suppose also that f sad − tsad and f 9sxd , t9sxd for a , x , b. Prove that f sbd , tsbd. [Hint: Apply the Mean Value Theorem to the function h − f 2 t.] 33. Show that sin x , x if 0 , x , 2.
; 19–20 Find the number c that satisfies the conclusion of the Mean Value Theorem on the given interval. Graph the function, the secant line through the endpoints, and the tangent line at sc, f scdd. Are the secant line and the tangent line parallel? 19. f sxd − sx , f0, 4g
20. f sxd − e2x, f0, 2g
21. Let f sxd − s x 2 3d22. Show that there is no value of c in s1, 4d such that f s4d 2 f s1d − f 9scds4 2 1d. Why does this not contradict the Mean Value Theorem?

34. S uppose f is an odd function and is differentiable everywhere. Prove that for every positive number b, there exists a number c in s2b, bd such that f 9scd − f sbdyb. 35. Use the Mean Value Theorem to prove the inequality
 sin a 2 sin b  <  a 2 b  for all a and b 36. If f 9sxd − c (c a constant) for all x, use Corollary 7 to show that f sxd − cx 1 d for some constant d. 37. Let f sxd − 1yx and

22. L et f sxd − 2 2 2 x 2 1 . Show that there is no value of c such that f s3d 2 f s0d − f 9scds3 2 0d. Why does this not contradict the Mean Value Theorem?
1 x
tsxd −
11
23–24 Show that the equation has exactly one real solution. 24. x 3 1 e x − 0
23. 2 x 1 cos x − 0
25. S how that the equation x 3 2 15x 1 c − 0 has at most one solution in the interval f22, 2g. 4
26. S how that the equation x 1 4x 1 c − 0 has at most two real solutions. 27. (a) Show that a polynomial of degree 3 has at most three real zeros. (b) Show that a polynomial of degree n has at most n real zeros. 28. (a) Suppose that f is differentiable on R and has two zeros. Show that f 9 has at least one zero. (b) Suppose f is twice differentiable on R and has three zeros. Show that f 0 has at least one real zero. (c) Can you generalize parts (a) and (b)? 29. If f s1d − 10 and f 9sxd > 2 for 1 < x < 4, how small can f s4d possibly be?
if x . 0 1 x
if x , 0
Show that f 9sxd − t9sxd for all x in their domains. Can we conclude from Corollary 7 that f 2 t is constant? 38–39 Use the method of Example 6 to prove the identity.
SD
38. arctan x 1 arctan
1 x
−
, x . 0 2
39. 2 sin21x − cos21s1 2 2x 2 d, x > 0 40. A t 2:00 pm a car’s speedometer reads 50 kmyh. At 2:10 pm it reads 65 kmyh. Show that at some time between 2:00 and 2:10 the acceleration is exactly 90 kmyh2. 41. T wo runners start a race at the same time and finish in a tie. Prove that at some time during the race they have the same speed. [Hint: Consider f std − tstd 2 hstd, where t and h are the position functions of the two runners.] 42. F ixed Points A number a is called a fixed point of a function f if f sad − a. Prove that if f 9sxd ± 1 for all real numbers x, then f has at most one fixed point.
4.3 What Derivatives Tell Us about the Shape of a Graph Many of the applications of calculus depend on our ability to deduce facts about a function f from information concerning its derivatives. Because f 9sxd represents the slope of the curve y − f sxd at the point sx, f sxdd, it tells us the direction in which the curve
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SECTION 4.3 What Derivatives Tell Us about the Shape of a Graph y
proceeds at each point. So it is reasonable to expect that information about f 9sxd will provide us with information about f sxd.
D B
■ What Does f 9 Say about f ?
C
A
297
x
0
FIGURE 1
Notation Let’s abbreviate the name of this test to the I/D Test.
To see how the derivative of f can tell us where a function is increasing or decreasing, look at Figure 1. (Increasing functions and decreasing functions were defined in Section 1.1.) Between A and B and between C and D, the tangent lines have positive slope and so f 9sxd . 0. Between B and C, the tangent lines have negative slope and so f 9sxd , 0. Thus it appears that f increases when f 9sxd is positive and decreases when f 9sxd is negative. To prove that this is always the case, we use the Mean Value Theorem. Increasing/Decreasing Test (a) If f 9sxd . 0 on an interval, then f is increasing on that interval. (b) If f 9sxd , 0 on an interval, then f is decreasing on that interval. PROOF (a) Let x 1 and x 2 be any two numbers in the interval with x1 , x2. According to the definition of an increasing function (Section 1.1), we have to show that f sx1 d , f sx2 d. Because we are given that f 9sxd . 0, we know that f is differentiable on fx1, x2 g. So, by the Mean Value Theorem, there is a number c between x1 and x2 such that f sx 2 d 2 f sx 1 d − f 9scdsx 2 2 x 1 d
1
Now f 9scd . 0 by assumption and x 2 2 x 1 . 0 because x 1 , x 2. Thus the right side of Equation 1 is positive, and so f sx 2 d 2 f sx 1 d . 0 or f sx 1 d , f sx 2 d This shows that f is increasing. Part (b) is proved similarly.
■
EXAMPLE 1 Find where the function f sxd − 3x 4 2 4x 3 2 12x 2 1 5 is increasing and where it is decreasing. SOLUTION We start by differentiating f : f 9sxd − 12x 3 2 12x 2 2 24x − 12xsx 2 2dsx 1 1d _1
FIGURE 2
0
2
x
To use the IyD Test we have to know where f 9sxd . 0 and where f 9sxd , 0. To solve these inequalities we first find where f 9sxd − 0, namely at x − 0, 2, and 21. These are the critical numbers of f , and they divide the domain into four intervals (see the number line in Figure 2). Within each interval, f 9sxd must be always positive or always negative. (See Examples 3 and 4 in Appendix A.) We can determine which is the case for each interval from the signs of the three factors of f 9sxd, namely, 12x, x 2 2, and x 1 1, as shown in the following chart. A plus sign indicates that the given expression is positive, and a minus sign indicates that it is negative. The last column of the chart gives the conclusion based on the IyD Test. For instance,
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
298
CHAPTER 4 Applications of Differentiation
f 9sxd , 0 for 0 , x , 2, so f is decreasing on (0, 2). (It would also be true to say that f is decreasing on the closed interval f0, 2g.)
20
_2
3
_30
FIGURE 3
Interval
12x
x22
x11
f 9sxd
f
x , 21 21 , x , 0 0,x,2 x.2
2 2 1 1
2 2 2 1
2 1 1 1
2 1 2 1
decreasing on s2`, 21d increasing on s21, 0d decreasing on s0, 2d increasing on s2, `d
The graph of f shown in Figure 3 confirms the information in the chart.
n
■ The First Derivative Test Recall from Section 4.1 that if f has a local maximum or minimum at c, then c must be a critical number of f (by Fermat’s Theorem), but not every critical number gives rise to a maximum or a minimum. We therefore need a test that will tell us whether or not f has a local maximum or minimum at a critical number. You can see from Figure 3 that for the function f in Example 1, f s0d − 5 is a local maximum value of f because f increases on s21, 0d and decreases on s0, 2d. Or, in terms of derivatives, f 9sxd . 0 for 21 , x , 0 and f 9sxd , 0 for 0 , x , 2. In other words, the sign of f 9sxd changes from positive to negative at 0. This observation is the basis of the following test. The First Derivative Test Suppose that c is a critical number of a continuous function f. (a) If f 9 changes from positive to negative at c, then f has a local maximum at c. (b) If f 9 changes from negative to positive at c, then f has a local minimum at c. (c) If f 9 is positive to the left and right of c, or negative to the left and right of c, then f has no local maximum or minimum at c. The First Derivative Test is a consequence of the IyD Test. In part (a), for instance, because the sign of f 9sxd changes from positive to negative at c, f is increasing to the left of c and decreasing to the right of c. It follows that f has a local maximum at c. It is easy to remember the First Derivative Test by visualizing diagrams such as those in Figure 4. y
y
fª(x)>0
y
fª(x) 0 for all x, we have f 0sxd , 0 for x , 0 and for 0 , x , 6 and f 0sxd . 0 for x . 6. So f is concave downward on s2`, 0d and s0, 6d and concave upward on s6, `d, and the only inflection point is s6, 0d. Using all of the information we gathered about f from its first and
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
304
CHAPTER 4 Applications of Differentiation
Try reproducing the graph in Figure 13 with a graphing calculator or computer. Some machines produce the complete graph, some produce only the portion to the right of the yaxis, and some produce only the portion between x − 0 and x − 6. For an explanation, see Example 7 in Graphing Calculators and Computers at www.StewartCalculus.com.
FIGURE 13
second derivatives, we sketch the graph in Figure 13. Note that the curve has vertical tangents at s0, 0d and s6, 0d because f 9sxd l ` as x l 0 and as x l 6.


y 4
(4, 2%?# )
3
2 0
1
2
3
4
5
7
x
y=x @ ?#(6x)!?#
n
EXAMPLE 8 Use the first and second derivatives of f sxd − e 1yx, together with asymptotes, to sketch its graph.

SOLUTION Notice that the domain of f is hx x ± 0j, so we check for vertical asymptotes by computing the left and right limits as x l 0. As x l 01, we know that t − 1yx l `, so lim e 1yx − lim e t − `
x l 01
tl`
and this shows that x − 0 is a vertical asymptote. As x l 02, we have t − 1yx l 2`, so lim e 1yx − lim e t − 0
x l 02
t l2`
As x l 6`, we have 1yx l 0 and so lim e 1yx − e 0 − 1
x l 6`
This shows that y − 1 is a horizontal asymptote (to both the left and right). Now let’s compute the derivative. The Chain Rule gives f 9sxd − 2
e 1yx x2
Since e 1yx . 0 and x 2 . 0 for all x ± 0, we have f 9sxd , 0 for all x ± 0. Thus f is decreasing on s2`, 0d and on s0, `d. There is no critical number, so the function has no local maximum or minimum. The second derivative is f 0sxd − 2
x 2e 1yxs21yx 2 d 2 e 1yxs2xd e 1yxs2x 1 1d − 4 x x4
Since e 1yx . 0 and x 4 . 0, we have f 0sxd . 0 when x . 212 sx ± 0d and f 0sxd , 0
when x , 212. So the curve is concave downward on (2`, 212 ) and concave upward on
(212 , 0) and on s0, `d. There is one inflection point: (212 , e22).
To sketch the graph of f we first draw the horizontal asymptote y − 1 (as a dashed line), together with the parts of the curve near the asymptotes in a preliminary sketch [Figure 14(a)]. These parts reflect the information concerning limits and the fact that f is decreasing on both s2`, 0d and s0, `d. Notice that we have indicated that f sxd l 0 as x l 02 even though f s0d does not exist. In Figure 14(b) we finish the Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
305
SECTION 4.3 What Derivatives Tell Us about the Shape of a Graph
sketch by incorporating the information concerning concavity and the inflection point. In Figure 14(c) we check our work with a computer. y
y
y=‰
4
inﬂection point y=1 0
y=1 0
x
(a) Preliminary sketch
_3
3
x
_1
(b) Finished sketch
(c) Computer conﬁrmation
FIGURE 14
n
4.3 Exercises 6. y
1–2 Use the given graph of f to find the following. (a) The open intervals on which f is increasing. (b) The open intervals on which f is decreasing. (c) The open intervals on which f is concave upward. (d) The open intervals on which f is concave downward. (e) The coordinates of the points of inflection. 1.
0
y=fª(x)
2
4
x
6
2. y
y
1
1 0
0
x
1
1
x
3. Suppose you are given a formula for a function f. (a) How do you determine where f is increasing or decreasing? (b) How do you determine where the graph of f is concave upward or concave downward? (c) How do you locate inflection points? 4. (a) State the First Derivative Test. (b) State the Second Derivative Test. Under what circum stances is it inconclusive? What do you do if it fails? 5–6 The graph of the derivative f 9 of a function f is shown. (a) On what intervals is f increasing? Decreasing? (b) At what values of x does f have a local maximum? Local minimum? 5. y
0
4
y
0
2
6
x
4
6
x
8
8. The graph of the first derivative f 9 of a function f is shown. (a) On what intervals is f increasing? Explain. (b) At what values of x does f have a local maximum or minimum? Explain. (c) On what intervals is f concave upward or concave downward? Explain. (d) What are the xcoordinates of the inflection points of f ? Why? y
y=fª(x) 2
7. In each part state the xcoordinates of the inflection points of f. Give reasons for your answers. (a) The curve is the graph of f . (b) The curve is the graph of f 9. (c) The curve is the graph of f 0.
0
y=fª(x) 2
4
6
8
x
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
306
CHAPTER 4 Applications of Differentiation
9–16 Find the intervals on which f is increasing or decreasing, and find the local maximum and minimum values of f .
34–41 Sketch the graph of a function that satisfies all of the given conditions.
9. f sxd − 2x 3 2 15x 2 1 24x 2 5
34. (a) f 9sxd , 0 and f 0sxd , 0 for all x (b) f 9sxd . 0 and f 0sxd . 0 for all x
10. f sxd − x 2 6x 2 135x 3
2
11. f sxd − 6x 4 2 16x 3 1 1 13. f sxd −
12. f sxd − x 2y3sx 2 3d
x 2 2 24 x25
14. f sxd − x 1
4 x2
15. f sxd − sin x 1 cos x, 0 < x < 2 16. f sxd − x 4 e2x 17–22 Find the intervals on which f is concave upward or concave downward, and find the inflection points of f . 17. f sxd − x 3 2 3x 2 2 9x 1 4
36. Vertical asymptote x − 0, f 9sxd . 0 if x , 22, f 9sxd , 0 if x . 22 sx ± 0d, f 0sxd , 0 if x , 0, f 0sxd . 0 if x . 0 37. f 9s0d − f 9s2d − f 9s4d − 0, f 9sxd . 0 if x , 0 or 2 , x , 4, f 9sxd , 0 if 0 , x , 2 or x . 4, f 0sxd . 0 if 1 , x , 3, f 0sxd , 0 if x , 1 or x . 3 38. f 9sxd . 0 for all x ± 1, vertical asymptote x − 1, f 99sxd . 0 if x , 1 or x . 3, f 99sxd , 0 if 1 , x , 3
18. f sxd − 2x 3 2 9x 2 1 12x 2 3 19. f sxd − sin2x 2 cos 2x, 0 < x < 20. f sxd − lns2 1 sin xd, 0 < x < 2 21. f sxd − lnsx 2 1 5d
35. (a) f 9sxd . 0 and f 0sxd , 0 for all x (b) f 9sxd , 0 and f 0sxd . 0 for all x
22. f sxd −
ex e 12 x
39. f 9s5d − 0, f 9sxd , 0 when x , 5, f 9sxd . 0 when x . 5, f 99s2d − 0, f 99s8d − 0, f 99sxd , 0 when x , 2 or x . 8, f 99sxd . 0 for 2 , x , 8, lim f sxd − 3, lim f sxd − 3 xl`
23–28 (a) Find the intervals on which f is increasing or decreasing. (b) Find the local maximum and minimum values of f . (c) Find the intervals of concavity and the inflection points. 23. f sxd − x 4 2 2x 2 1 3
x 24. f sxd − 2 x 11
25. f sxd − x 2 2 x 2 ln x
26. f sxd − x 2 ln x
27. f sxd − xe 2x 28. f sxd − cos2 x 2 2 sin x, 0 < x < 2
31. Suppose the derivative of a function f is f 9sxd − sx 2 4d sx 1 3d sx 2 5d 2
7
x l2
x l2
f 99sxd . 0 if 21 , x , 2 or 2 , x , 4, f 0sxd , 0 if x . 4 41. f 9sxd . 0 if x ± 2, f 99sxd . 0 if x , 2, f 99sxd , 0 if x . 2, f has inflection point s2, 5d, lim f sxd − 8, lim f sxd − 0 xl`
29–30 Find the local maximum and minimum values of f using both the First and Second Derivative Tests. Which method do you prefer? x2 29. f sxd − 1 1 3x 2 2 2x 3 30. f sxd − x21
8
On what interval(s) is f increasing? 32. (a) Find the critical numbers of f sxd − x 4sx 2 1d3. (b) What does the Second Derivative Test tell you about the behavior of f at these critical numbers? (c) What does the First Derivative Test tell you? 33. Suppose f 0 is continuous on s2`, `d. (a) If f 9s2d − 0 and f 0s2d − 25, what can you say about f ? (b) If f 9s6d − 0 and f 0s6d − 0, what can you say about f ?
xl 2`
40. f 9s0d − f 9s4d − 0, f 9sxd − 1 if x , 21, f 9sxd . 0 if 0 , x , 2, f 9sxd , 0 if 21 , x , 0 or 2 , x , 4 or x . 4, lim2 f 9sxd − `, lim1 f 9sxd − 2`,
xl 2`
42. T he graph of a function y − f sxd is shown. At which point(s) are the following true? dy d 2y (a) and are both positive. dx dx 2
dy d 2y (b) and are both negative. dx dx 2
dy d 2y (c) is negative but is positive. dx dx 2 y C A
0
D
E
B x
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SECTION 4.3 What Derivatives Tell Us about the Shape of a Graph
43–44 The graph of the derivative f 9 of a continuous function f is shown. (a) On what intervals is f increasing? Decreasing? (b) At what values of x does f have a local maximum? Local minimum? (c) On what intervals is f concave upward? Concave downward? (d) State the xcoordinate(s) of the point(s) of inflection. (e) Assuming that f s0d − 0, sketch a graph of f . 43.
y
y=fª(x)
2 0
y
2
4
ex 1 2 ex
63. f sxd − e 2x
64. f sxd − x 2 16 x 2 2 23 ln x
65. f sxd − lns1 2 ln xd
66. f sxd − e arctan x
2
67–68 Use the methods of this section to sketch several members of the given family of curves. What do the members have in common? How do they differ from each other? 68. f sxd − x 3 2 3c 2 x 1 2c 3, c . 0
8 x
6
; 69–70 (a) Use a graph of f to estimate the maximum and minimum values. Then find the exact values. (b) Estimate the value of x at which f increases most rapidly. Then find the exact value.
y=fª(x)
2 0
62. f sxd −
67. f sxd − x 4 2 cx, c . 0
_2
44.
61. f sxd − e22yx
307
2
4
69. f sxd −
8 x
6
_2
45–58 (a) Find the intervals of increase or decrease. (b) Find the local maximum and minimum values. (c) Find the intervals of concavity and the inflection points. (d) Use the information from parts (a) – (c) to sketch the graph. You may want to check your work with a graphing calculator or computer. 45. f sxd − x 3 2 3x 2 1 4
46. f sxd − 36x 1 3x 2 2 2x 3
47. f sxd − 12 x 4 2 4x 2 1 3
48. tsxd − 200 1 8x 3 1 x 4
49. tstd − 3t 2 8t 1 12
50. hsxd − 5x 2 3x
51. f szd − z 2 112z 2
52. f sxd − sx 2 2 4d3
53. Fsxd − x s6 2 x
54. G sxd − 5x 2y3 2 2x 5y3
55. Csxd − x 1y3sx 1 4d
56. f sxd − lnsx 2 1 9d
4
3
7
3
72. f sxd − sx 2 1d2 sx 1 1d3 73–74 Estimate the intervals of concavity to one decimal place by using a computer algebra system to compute and graph f 0. 73. f sxd −
59–66 (a) Find the vertical and horizontal asymptotes. (b) Find the intervals of increase or decrease. (c) Find the local maximum and minimum values. (d) Find the intervals of concavity and the inflection points. (e) Use the information from parts (a) – (d) to sketch the graph of f. x2 2 4 x2 1 4
x4 1 x3 1 1 sx 2 1 x 1 1
74. f sxd −
x 2 tan21 x 1 1 x3
5
75. A graph of a population of yeast cells in a new laboratory culture as a function of time is shown. 700
Number of yeast cells
58. Ssxd − x 2 sin x, 0 < x < 4
60. f sxd −
70. f s xd − x 2 e2x
71. f sxd − sin 2x 1 sin 4x, 0 < x <
57. f sd − 2 cos 1 cos , 0 < < 2
1 1 2 2 x x
sx 2 1 1
; 71–72 (a) Use a graph of f to give a rough estimate of the intervals of concavity and the coordinates of the points of inflection. (b) Use a graph of f 0 to give better estimates.
2
59. f sxd − 1 1
x11
600 500 400 300 200 100
0
2
4
6
8
10 12 14 16 18
Time (in hours)
(a) Describe how the rate of population increase varies. (b) When is this rate highest? (c) On what intervals is the population function concave upward or downward? (d) Estimate the coordinates of the inflection point.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
308
CHAPTER 4 Applications of Differentiation
76. I n an episode of The Simpsons television show, Homer reads from a newspaper and announces “Here’s good news! According to this eyecatching article, SAT scores are declining at a slower rate.” Interpret Homer’s statement in terms of a function and its first and second derivatives. 77. T he president announces that the national deficit is increasing, but at a decreasing rate. Interpret this statement in terms of a function and its first and second derivatives. 78. L et f std be the temperature at time t where you live and suppose that at time t − 3 you feel uncomfortably hot. How do you feel about the given data in each case? (a) f 9s3d − 2, f 0s3d − 4 (b) f 9s3d − 2, f 0s3d − 24 (c) f 9s3d − 22, f 0s3d − 4 (d) f 9s3d − 22, f 0s3d − 24 79. L et Kstd be a measure of the knowledge you gain by studying for a test for t hours. Which do you think is larger, Ks8d 2 Ks7d or Ks3d 2 Ks2d? Is the graph of K concave upward or concave downward? Why? 80. C offee is being poured into the mug shown in the figure at a constant rate (measured in volume per unit time). Sketch a rough graph of the depth of the coffee in the mug as a function of time. Account for the shape of the graph in terms of concavity. What is the significance of the inflection point?
drug response curve describes the level of medication in ; 81. A the bloodstream after a drug is administered. A surge function Sstd − At pe2kt is often used to model the response curve, reflecting an initial surge in the drug level and then a more gradual decline. If, for a particular drug, A − 0.01, p − 4, k − 0.07, and t is measured in minutes, estimate the times corresponding to the inflection points and explain their significance. Then graph the drug response curve. 82. Normal Density Functions The family of bellshaped curves y−
1 s2
e2sx2d ys2 2
2
d
occurs in probability and statistics, where it is called the normal density function. The constant is called the mean and the positive constant is called the standard deviation. For simplicity, let’s scale the function so as to remove the factor 1y( s2 ) and let’s analyze the special case where − 0. So we study the function f sxd − e2x
ys2 2 d
2
(a) Find the asymptote, maximum value, and inflection points of f .
;
(b) What role does play in the shape of the curve? (c) Illustrate by graphing four members of this family on the same screen.
83. F ind a cubic function f sxd − ax 3 1 bx 2 1 cx 1 d that has a local maximum value of 3 at x − 22 and a local minimum value of 0 at x − 1. 84. For what values of the numbers a and b does the function f sxd − axe bx
2
have the maximum value f s2d − 1? 85. S how that the curve y − s1 1 xdys1 1 x 2 d has three points of inflection and they all lie on one straight line. 86. S how that the curves y − e 2x and y − 2e2x touch the curve y − e2x sin x at its inflection points. 87. S how that the inflection points of the curve y − x sin x lie on the curve y 2sx 2 1 4d − 4x 2. 88–90 Assume that all of the functions are twice differentiable and the second derivatives are never 0. 88. (a) If f and t are concave upward on an interval I, show that f 1 t is concave upward on I. (b) If f is positive and concave upward on I, show that the function tsxd − f f sxdg 2 is concave upward on I. 89. (a) If f and t are positive, increasing, concave upward functions on an interval I, show that the product function f t is concave upward on I. (b) Show that part (a) remains true if f and t are both decreasing. (c) Suppose f is increasing and t is decreasing. Show, by giving three examples, that f t may be concave upward, concave downward, or linear. Why doesn’t the argument in parts (a) and (b) work in this case? 90. S uppose f and t are both concave upward on s2`, `d. Under what condition on f will the composite function hsxd − f s tsxdd be concave upward? 91. S how that a cubic function (a thirddegree polynomial) always has exactly one point of inflection. If its graph has three xintercepts x 1 , x 2 , and x 3 , show that the xcoordinate of the inflection point is sx 1 1 x 2 1 x 3 dy3. or what values of c does the polynomial ; 92. F Psxd − x 4 1 cx 3 1 x 2 have two inflection points? One inflection point? None? Illustrate by graphing P for several values of c. How does the graph change as c decreases? 93. P rove that if sc, f scdd is a point of inflection of the graph of f and f 0 exists in an open interval that contains c, then f 0scd − 0. [Hint: Apply the First Derivative Test and Fermat’s Theorem to the function t − f 9.] 94. S how that if f sxd − x 4, then f 0s0d − 0, but s0, 0d is not an inflection point of the graph of f .
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.4 Indeterminate Forms and l’Hospital’s Rule
 
95. S how that the function tsxd − x x has an inflection point at s0, 0d but t0s0d does not exist.
99. T he three cases in the First Derivative Test cover the situations commonly encountered but do not exhaust all possibilities. Consider the functions f, t, and h whose values at 0 are all 0 and, for x ± 0,
96. Suppose that f 09 is continuous and f 9scd − f 0scd − 0, but f scd . 0. Does f have a local maximum or minimum at c ? Does f have a point of inflection at c?
f sxd − x 4 sin
hsxd − x 4 22 1 sin
98. For what values of c is the function 1 x2 1 3
increasing on s2`, `d?
S D
1 1 tsxd − x 4 2 1 sin x x
S
97. S uppose f is differentiable on an interval I and f 9sxd . 0 for all numbers x in I except for a single number c. Prove that f is increasing on the entire interval I.
f sxd − cx 1
309
D
1 x
(a) Show that 0 is a critical number of all three functions but their derivatives change sign infinitely often on both sides of 0. (b) Show that f has neither a local maximum nor a local minimum at 0, t has a local minimum, and h has a local maximum.
4.4 Indeterminate Forms and l’Hospital’s Rule Suppose we are trying to analyze the behavior of the function Fsxd −
ln x x21
Although F is not defined when x − 1, we need to know how F behaves near 1. In particular, we would like to know the value of the limit 1
lim
x l1
ln x x21
In computing this limit we can’t apply Law 5 of limits (the limit of a quotient is the quo tient of the limits, see Section 2.3) because the limit of the denominator is 0. In fact, although the limit in (1) exists, its value is not obvious because both numerator and denominator approach 0 and 00 is not defined.
■ Indeterminate Forms (Types 00, ` `) In general, if we have a limit of the form lim
xla
f sxd tsxd
where both f sxd l 0 and tsxd l 0 as x l a, then this limit may or may not exist and is called an indeterminate form of type 00. We met some limits of this type in Chapter 2. For rational functions, we can cancel common factors: lim
x l1
x2 2 x xsx 2 1d x 1 − lim − lim − x l1 sx 1 1dsx 2 1d x l1 x 1 1 x2 2 1 2
In Section 3.3 we used a geometric argument to show that lim
xl0
sin x −1 x
But these methods do not work for limits such as (1). Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
310
CHAPTER 4 Applications of Differentiation
Another situation in which a limit is not obvious occurs when we look for a horizontal asymptote of F and need to evaluate the limit 2
lim
xl`
ln x x21
It isn’t obvious how to evaluate this limit because both numerator and denominator become large as x l `. There is a struggle between numerator and denominator. If the numerator wins, the limit will be ` (the numerator was increasing significantly faster than the denominator); if the denominator wins, the answer will be 0. Or there may be some compromise, in which case the answer will be some finite positive number. In general, if we have a limit of the form lim
xla
y
where both f sxd l ` (or 2`) and tsxd l ` (or 2`), then the limit may or may not exist and is called an indeterminate form of type ` `. We saw in Section 2.6 that this type of limit can be evaluated for certain functions, including rational functions, by dividing numerator and denominator by the highest power of x that occurs in the denominator. For instance,
f
1 x 21 x2 120 1 lim − lim − − 2 x l ` 2x 1 1 xl` 1 210 2 21 2 x
g 0
a
y
f sxd tsxd
12
2
x
But this method does not work for limits such as (2).
y=m¡(xa)
■ L’Hospital’s Rule We now introduce a systematic method, known as l’Hospital’s Rule, for the evaluation of indeterminate forms of type 00 or type ` `.
y=m™(xa) 0
a
x
FIGURE 1 Figure 1 suggests visually why l’Hospital’s Rule might be true. The first graph shows two differentiable functions f and t, each of which approaches 0 as x l a. If we were to zoom in toward the point sa, 0d, the graphs would start to look almost linear. But if the functions actually were linear, as in the second graph, then their ratio would be m1sx 2 ad m1 − m2sx 2 ad m2 which is the ratio of their derivatives. This suggests that f sxd f 9sxd lim − lim x l a tsxd x l a t9sxd
L’Hospital’s Rule Suppose f and t are differentiable and t9sxd ± 0 on an open interval I that contains a (except possibly at a). Suppose that lim f sxd − 0 and lim tsxd − 0
xla
or that
xla
lim f sxd − 6` and lim tsxd − 6`
xla
xla
(In other words, we have an indeterminate form of type 00 or ``.) Then lim
xla
f sxd f 9sxd − lim x l a t9sxd tsxd
if the limit on the right side exists (or is ` or 2`). NOTE 1 L’Hospital’s Rule says that the limit of a quotient of functions is equal to the limit of the quotient of their derivatives, provided that the given conditions are satisfied. It is especially important to verify the conditions regarding the limits of f and t before using l’Hospital’s Rule.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
SECTION 4.4 Indeterminate Forms and l’Hospital’s Rule
L’Hospital L’Hospital’s Rule is named after a French nobleman, the Marquis de l’Hospital (1661–1704), but was discovered by a Swiss mathematician, John Bernoulli (1667–1748). You might sometimes see l’Hospital spelled as l’Hôpital, but he spelled his own name l’Hospital, as was common in the 17th century. See Exercise 85 for the example that the Marquis used to illustrate his rule. See the project following this section for further historical details.
311
NOTE 2 L’Hospital’s Rule is also valid for onesided limits and for limits at infinity or negative infinity; that is, “x l a” can be replaced by any of the symbols x l a1, x l a2, x l `, or x l 2`. NOTE 3 For the special case in which f sad − tsad − 0, f 9 and t9 are continuous, and t9sad ± 0, it is easy to see why l’Hospital’s Rule is true. In fact, using the alternative form of the definition of a derivative (2.7.5), we have
f sxd 2 f sad f 9sxd f 9sad x2a lim − − x l a t9sxd t9sad tsxd 2 tsad lim xla x2a lim
xla
f sxd 2 f sad x2a − lim x l a tsxd 2 tsad x2a f sxd 2 f sad f sxd − lim − lim fbecause f sad − tsad − 0g x l a tsxd 2 tsad x l a tsxd It is more difficult to prove the general version of l’Hospital’s Rule. See Appendix F.
EXAMPLE 1 Find lim
xl1
ln x . x21
SOLUTION Since lim ln x − ln 1 − 0 and lim sx 2 1d − 0
x l1
x l1
the limit is an indeterminate form of type Notice that when using l’Hospital’s Rule we differentiate the numerator and denominator separately. We do not use the Quotient Rule.
The graph of the function of Example 2 is shown in Figure 2. We have noticed previously that exponential functions grow far more rapidly than power functions, so the result of Example 2 is not unexpected. See also Exercise 75.
0
FIGURE 2
´ ≈
so we can apply l’Hospital’s Rule:
d sln xd ln x dx 1yx lim − lim − lim xl1 x 2 1 xl1 d xl1 1 sx 2 1d dx 1 − lim − 1 xl1 x
EXAMPLE 2 Calculate lim
xl`
n
ex . x2
SOLUTION We have lim x l ` e x − ` and lim x l ` x 2 − `, so the limit is an indeterminate form of type ` ` , and l’Hospital’s Rule gives d se x d ex dx ex lim 2 − lim − lim xl` x xl` d x l ` 2x sx 2 d dx
20
y=
0 0 ,
Since e x l ` and 2x l ` as x l `, the limit on the right side is also indeterminate. A second application of l’Hospital’s Rule gives 10
lim
xl`
ex ex ex − lim − lim − ` x l ` 2x xl` 2 x2
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312
CHAPTER 4 Applications of Differentiation
The graph of the function of Example 3 is shown in Figure 3. We have discussed previously the slow growth of logarithms, so it isn’t surprising that this ratio approaches 0 as x l `. See also Exercise 76. 2
EXAMPLE 3 Calculate lim
ln x
xl`
sx
.
SOLUTION Since ln x l ` and sx l ` as x l `, l’Hospital’s Rule applies: lim
xl`
ln x sx
− lim
1yx
1 x l ` x21y2 2
− lim
xl `
1yx 1y(2sx
)
Notice that the limit on the right side is now indeterminate of type 00. But instead of applying l’Hospital’s Rule a second time as we did in Example 2, we simplify the expression and see that a second application is unnecessary:
y= ln x œ„ x 0
10,000
_1
lim
xl`
ln x
− lim
sx
xl`
1yx 1y(2sx )
− lim
xl`
2 sx
−0
n
In both Examples 2 and 3 we evaluated limits of type ` ` , but we got two different results. In Example 2, the infinite limit tells us that the numerator e x increases significantly faster than the denominator x 2, resulting in larger and larger ratios. In fact, y − e x grows more quickly than all the power functions y − x n (see Exercise 75). In Example 3 we have the opposite situation; the limit of 0 means that the denominator outpaces the numerator, and the ratio eventually approaches 0.
FIGURE 3
EXAMPLE 4 Find lim
xl0
tan x 2 x . (See Exercise 2.2.48.) x3
SOLUTION Noting that both tan x 2 x l 0 and x 3 l 0 as x l 0, we use l’Hospital’s Rule: lim
xl0
tan x 2 x sec2x 2 1 − lim xl0 x3 3x 2
Since the limit on the right side is still indeterminate of type 00, we apply l’Hospital’s Rule again:
The graph in Figure 4 gives visual confirmation of the result of Example 4. If we were to zoom in too far, however, we would get an inaccurate graph because tan x is close to x when x is small. See Exercise 2.2.48(d). 1
0
FIGURE 4
xl0
sec2x 2 1 2 sec2x tan x − lim xl0 3x 2 6x
Because lim x l 0 sec2 x − 1, we simplify the calculation by writing lim
xl0
2 sec2x tan x 1 tan x 1 tan x − lim sec2 x lim − lim x l 0 x l 0 xl 0 6x 3 x 3 x
We can evaluate this last limit either by using l’Hospital’s Rule a third time or by writing tan x as ssin xdyscos xd and making use of our knowledge of trigonometric limits. Putting together all the steps, we get y=
_1
lim
tan x x ˛
lim
xl0
1
tan x 2 x sec 2 x 2 1 2 sec 2 x tan x − lim − lim 3 2 xl0 xl0 x 3x 6x −
1 tan x 1 sec 2 x 1 lim − lim − 3 xl0 x 3 xl0 1 3
n
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SECTION 4.4 Indeterminate Forms and l’Hospital’s Rule
EXAMPLE 5 Find lim 2 xl
313
sin x . 1 2 cos x
SOLUTION If we blindly attempted to use l’Hospital’s Rule, we might think that an equivalent limit is cos x lim − 2` x l 2 sin x This is wrong! Although the numerator sin x l 0 as x l 2, notice that the denominator s1 2 cos xd does not approach 0, so l’Hospital’s Rule can’t be applied here. The required limit can, in fact, be found by direct substitution because the function is continuous at and the denominator is nonzero there:
sin x sin 0 − − − 0 1 2 cos x 1 2 cos 1 2 s21d
lim
x l 2
n
Example 5 shows what can go wrong if you use l’Hospital’s Rule without thinking. Some limits can be found using l’Hospital’s Rule but are more easily found by other methods. (See Examples 2.3.3, 2.3.5, and 2.6.3, and the discussion at the beginning of this section.) When evaluating any limit, you should consider other methods before using l’Hospital’s Rule.
■ Indeterminate Products (Type 0 ?`) If lim x l a f sxd − 0 and lim x l a tsxd − ` (or 2`), then it isn’t clear what the value of lim x l a f f sxd tsxdg, if any, will be. There is a struggle between f and t. If f wins, the answer will be 0; if t wins, the answer will be ` (or 2`). Or there may be a compromise where the answer is a finite nonzero number. For instance, lim1 x 2 − 0,
xl0
lim1 x − 0,
lim1
xl0
xl0
xl0
lim1 x − 0,
xl0
Figure 5 shows the graph of the function in Example 6. Notice that the function is undefined at x − 0 ; the graph approaches the origin but never quite reaches it.
1 1 − ` and lim1 x 2 ? − lim1 x − 0 xl0 xl0 x x
lim1
1 1 1 −` 2 − ` and lim1 x ? 2 − lim1 xl0 xl0 x x x
lim1
xl0
1 1 − ` and lim1 x ? − lim11 − 1 xl0 xl0 x x
This kind of limit is called an indeterminate form of type 0 `. We can deal with it by writing the product ft as a quotient: ft −
f t or ft − 1yt 1yf
This converts the given limit into an indeterminate form of type 00 or ` ` so that we can use l’Hospital’s Rule.
y
y=x ln x
EXAMPLE 6 Evaluate lim1 x ln x. x l0
0
1
FIGURE 5
x
SOLUTION The given limit is indeterminate because, as x l 0 1, the first factor sxd approaches 0 while the second factor sln xd approaches 2`. Writing x − 1ys1yxd, we have 1yx l ` as x l 0 1, so l’Hospital’s Rule gives
lim x ln x − lim1
x l 01
xl0
ln x 1yx − lim1 − lim1 s2xd − 0 x l 0 21yx 2 xl0 1yx
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n
314
CHAPTER 4 Applications of Differentiation
NOTE In solving Example 6 another possible option would have been to write
lim1 x ln x − lim1
xl0
xl0
x 1yln x
This gives an indeterminate form of the type 00, but if we apply l’Hospital’s Rule we get a more complicated expression than the one we started with. In general, when we rewrite an indeterminate product, we try to choose the option that leads to the simpler limit.
■ Indeterminate Differences (Type ` 2 `) If lim x l a f sxd − ` and lim x l a tsxd − `, then the limit lim f f sxd 2 tsxdg
xla
is called an indeterminate form of type `2`. Again there is a contest between f and t. Will the answer be ` ( f wins) or will it be 2` ( t wins) or will they compromise on a finite number? To find out, we try to convert the difference into a quotient (for instance, by using a common denominator, or rationalization, or factoring out a common factor) so that we have an indeterminate form of type 00 or ` `.
EXAMPLE 7 Compute lim1 x l1
S
D
1 1 2 . ln x x21
SOLUTION First notice that 1ysln xd l ` and 1ysx 2 1d l ` as x l 11, so the limit is indeterminate of type `2 `. Here we can start with a common denominator: lim
x l11
S
1 1 2 ln x x21
D
− lim1 x l1
x 2 1 2 ln x sx 2 1d ln x
Both numerator and denominator have a limit of 0, so l’Hospital’s Rule applies, giving x 2 1 2 ln x lim − lim1 x l11 sx 2 1d ln x x l1
1 x x21 − lim1 x l1 1 x 2 1 1 x ln x sx 2 1d 1 ln x x 12
Again we have an indeterminate limit of type 00, so we apply l’Hospital’s Rule a second time: lim
x l11
x21 − lim1 x l1 x 2 1 1 x ln x
− lim1 x l1
1 1 1 1 x 1 ln x x 1 1 − 2 1 ln x 2
n
EXAMPLE 8 Calculate lim se x 2 xd. xl`
SOLUTION This is an indeterminate difference because both e x and x approach infinity. We would expect the limit to be infinity because e x l ` much faster than x. But we can verify this by factoring out x: ex 2 x − x
S D ex 21 x
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SECTION 4.4 Indeterminate Forms and l’Hospital’s Rule
315
The term e xyx l ` as x l ` by l’Hospital’s Rule and so we now have a product in which both factors grow large:
F S DG
lim se x 2 xd − lim x
xl`
xl`
ex 21 x
− `
n
■ Indeterminate Powers (Types 00, `0, 1`) Several indeterminate forms arise from the limit lim f f sxdg tsxd
x la
1. lim f sxd − 0 and lim tsxd − 0 type 0 0 xla
xla
2. lim f sxd − ` and lim tsxd − 0 type ` 0 xla
xla
3. lim f sxd − 1 and lim tsxd − 6` type 1` xla
Although forms of the type 0 0, `0, and 1` are indeterminate, the form 0 ` is not indeterminate. (See Exercise 88.)
xla
Each of these three cases can be treated either by taking the natural logarithm: let y − f f sxdg tsxd, then ln y − tsxd ln f sxd or by using Formula 1.5.10 to write the function as an exponential: f f sxdg tsxd − e tsxd ln f sxd (Recall that both of these methods were used in differentiating such functions.) In either method we are led to the indeterminate product tsxd ln f sxd, which is of type 0 `.
EXAMPLE 9 Calculate lim1 s1 1 sin 4xdcot x. xl0
SOLUTION First notice that as x l 0 1, we have 1 1 sin 4x l 1 and cot x l `, so the given limit is indeterminate (type 1` ). Let y − s1 1 sin 4xdcot x Then
ln y − ln fs1 1 sin 4xdcot x g − cot x ln s1 1 sin 4xd −
ln s1 1 sin 4xd tan x
so l’Hospital’s Rule gives The graph of the function y − x x, x . 0, is shown in Figure 6. Notice that although 0 0 is not defined, the values of the function approach 1 as x l 01. This confirms the result of Example 10. 2
4 cos 4x ln s1 1 sin 4xd 1 1 sin 4x lim ln y − lim1 − lim1 −4 x l 01 xl 0 xl0 tan x sec2x So far we have computed the limit of ln y, but what we want is the limit of y. To find this we use the fact that y − e ln y:
lim s1 1 sin 4xdcot x − lim1 y − lim1 e ln y − e 4
x l 01
xl0
xl0
n
EXAMPLE 10 Find lim1 x x. xl0
_1
FIGURE 6
0
2
SOLUTION Notice that this limit is indeterminate since 0 x − 0 for any x . 0 but x 0 − 1 for any x ± 0. (Recall that 0 0 is undefined.) We could proceed as in Example 9 or by writing the function as an exponential: x x − se ln x d x − e x ln x
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316
CHAPTER 4 Applications of Differentiation
In Example 6 we used l’Hospital’s Rule to show that lim x ln x − 0
x l 01
lim x x − lim1 e x ln x − e 0 − 1
Therefore
x l 01
n
xl0
4.4 Exercises 1–4 Given that lim tsxd − 0
lim f sxd − 0
xla
xla
lim psxd − `
xla
7. The graph of a function f and its tangent line at 0 are shown. f sxd What is the value of lim x ? xl0 e 2 1
lim hsxd − 1
xla
lim qs xd − `
xla
y
which of the following limits are indeterminate forms? For any limit that is not an indeterminate form, evaluate it where possible. 1. (a) lim
f sxd f sxd (b) lim x l a psxd tsxd
(c) lim
hsxd psxd (d) lim x l a f sxd psxd
xla
xla
y=ƒ 0
2. (a) lim f f sxdpsxdg (b) lim fhsxdpsxdg xla
8. lim
x23 x2 2 9
9. lim
x 2 2 2x 2 8 x24
10. lim
11. lim
x7 2 1 x3 2 1
12. lim
sx 2 2 x24
14. lim
tan 3x sin 2x
xl3
(c) lim f psxdqsxdg xla
x l4
3. (a) lim f f sxd 2 psxdg (b) lim f psxd 2 qsxdg xla
xla
(c) lim f psxd 1 qsxdg
x l1
xla
4. (a) lim f f sxdg tsxd (b) lim f f sxdg psxd
13. lim
xla
xl a
(c) lim fhsxdg psxd
(d) lim f psxdg f sxd
(e) lim f psxdg
(f ) lim spsxd
xla xla
x l y4
xla
qsxd
qsxd
y=1.8(x2)
6.
f
y
0
2 4
x
y=5 (x2)
x2 1 2 cos x
17. lim
sin sx 2 1d x3 1 x 2 2
18. lim
1 1 cos 1 2 cos
19. lim
sx 1 1 ex
20. lim
x 1 x2 1 2 2x 2
22. lim
ln sx x2
xl1
xl`
0
x
g
y=2x
ln x x
x l0
l
xl`
xl`
23. lim
ln sxy3d 32x
24. lim
8t 2 5t t
25. lim
s1 1 2x 2 s1 2 4x x
26. lim
e uy10 u3
28. lim
sinh x 2 x x3
xl3
2
xl0
16. lim
xl0
f
g
x l4
x3 1 8 x12
e 2t 2 1 sin t
21. lim1
y=1.5(x2)
sin x 2 cos x tan x 2 1
x l 22
15. lim
tl0
xla
5–6 Use the graphs of f and t and their tangent lines at s2, 0d to f sxd find lim . x l 2 tsxd 5. y
x
8–70 Find the limit. Use l’Hospital’s Rule where appropriate. If there is a more elementary method, consider using it. If l’Hospital’s Rule doesn’t apply, explain why.
psxd (e) lim x l a qsxd xla
y=x
xl0
x
27. lim
xl0
e 1e 22 ex 2 x 2 1
tl0
ul `
2x
xl0
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SECTION 4.4 Indeterminate Forms and l’Hospital’s Rule
; 73–74 Illustrate l’Hospital’s Rule by graphing both f sxdytsxd and f 9sxdyt9sxd near x − 0 to see that these ratios have the same limit as x l 0. Also, calculate the exact value of the limit.
29. lim
tanh x tan x
30. lim
x 2 sin x x 2 tan x
31. lim
sin21x x
32. lim
sln xd2 x
33. lim
x3x 3 21
34. lim
e x 1 e2x 2 2 cos x x sin x
74. f sxd − 2x sin x, tsxd − sec x 2 1
35. lim
lns1 1 xd cos x 1 e x 2 1
36. lim
x sinsx 2 1d 2x 2 2 x 2 1
75. Prove that
xl0
xl0
xl0
xl0
xl0
xl`
x
xl0
xl1
73. f sxd − e x 2 1, tsxd − x 3 1 4x
xa 2 1 , b ± 0 xb 2 1
40. lim
xl`
e2x sy2d 2 tan21x
x 2 sin x 42. lim x l 0 x sinsx 2 d
43. lim x sinsyxd
44. lim sx e2xy2
45. lim sin 5x csc 3x
46. lim x ln 1 2
xl`
xl`
2
50.
53. lim1 x l0
55. lim1 xl0
77–78 What happens if you try to use l’Hospital’s Rule to find the limit? Evaluate the limit using another method.
1 x
49. lim1 ln x tans xy2d
S S
77. lim
xl `
xl`
D D
52. lim scsc x 2 cot xd
1 1 2 x x e 21
54. lim1
xl0
xl0
S
1 1 2 x tan21 x
D
57. lim1 x sx
58. lim1 stan 2xd x
59. lim s1 2 2xd1yx
60. lim
61. lim1 x 1ys12xd
62. lim se x 1 10xd1yx
xl0
xl`
x l1
S D 11
a x
bx
xl`
1yx
2x
63. lim x
64. lim x e
65. lim1 s4x 1 1d cot x
66. lim1 s1 2 cos xd sin x
xl`
xl`
67. lim1 s1 1 sin 3xd 1yx
xl0
68. lim scos xd1yx xl0
x
69. lim1 x l0
x l0
x l0
x 21 ln x 1 x 2 1
78.
70. lim
xl`
S
2
2x 2 3 2x 1 5
D
2x11
; 71–72 Use a graph to estimate the value of the limit. Then use l’Hospital’s Rule to find the exact value.
S D
x
xl`
11
2 x
sec x tan x
where t is the acceleration due to gravity and c is a positive constant. (In Chapter 9 we will be able to deduce this equation from the assumption that the air resistance is propor tional to the speed of the object; c is the proportionality constant.) (a) Calculate lim t l ` v. What is the meaning of this limit? (b) For fixed t, use l’Hospital’s Rule to calculate lim cl 01 v. What can you conclude about the velocity of a falling object in a vacuum?
81. I f an initial amount A0 of money is invested at an interest rate r compounded n times a year, the value of the invest ment after t years is
S D
A − A0 1 1
71. lim
lim
x l sy2d2
80. I f an object with mass m is dropped from rest, one model for its speed v after t seconds, taking air resistance into account, is mt v− s1 2 e 2ctym d c
xl`
xl0
x ; 79. I nvestigate the family of curves f sxd − e 2 cx. In particular, find the limits as x l 6` and determine the values of c for which f has an absolute minimum. What happens to the minimum points as c increases?
56. lim sx 2 ln xd
x l0
x sx 2 1 1
lim cos x sec 5x
x l sy2d2
x 1 2 x21 ln x
1 1 2 x tan x
ln x −0 xp
for any number p . 0. This shows that the logarithmic function approaches infinity more slowly than any power of x.
48. lim x 3y2 sins1yxd
xl1
lim
xl`
47. lim x 3e 2x xl`
76. Prove that
S D
x l 2`
xl0
51. lim
xl`
ex −` xn
for any positive integer n. This shows that the exponential function approaches infinity faster than any power of x.
cos x 2 1 1 12 x 2 41. lim xl0 x4
x l1
lim
x 2 sin x 38. lim x l 0 sin x 2 x
arctan 2x 37. lim1 xl0 ln x 39. lim
xl1
317
x
72. lim
xl0
x
5 24 3x 2 2x
r n
nt
If we let n l `, we refer to the continuous compounding of interest. Use l’Hospital’s Rule to show that if interest is compounded continuously, then the amount after t years is A − A0 e rt
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
318
CHAPTER 4 Applications of Differentiation
the carrying capacity and represents the maximum population size that can be supported, and
82. L ight enters the eye through the pupil and strikes the retina, where photoreceptor cells sense light and color. W. Stanley Stiles and B. H. Crawford studied the phenomenon in which measured brightness decreases as light enters farther from the center of the pupil (see the figure).
A−
B
A
84. A metal cable has radius r and is covered by insulation so that the distance from the center of the cable to the exterior of the insulation is R. The velocity v of an electrical impulse in the cable is r 2 r v − 2c ln R R
A light beam A that enters through the center of the pupil measures brighter than a beam B entering near the edge of the pupil.
SD SD
They detailed their findings of this phenomenon, known as the Stiles– Crawford effect of the first kind, in an important paper published in 1933. In particular, they observed that the amount of luminance sensed was not proportional to the area of the pupil as they expected. The percentage P of the total luminance entering a pupil of radius r mm that is sensed at the retina can be described by
where c is a positive constant. Find the following limits and interpret your answers. (a) lim1 v (b) lim1 v R lr
r l0
85. T he first appearance in print of l’Hospital’s Rule was in the book Analyse des infiniment petits published by the Marquis de l’Hospital in 1696. This was the first calculus textbook ever published. The example that the Marquis used in that book to illustrate his rule was to find the limit of the function y−
P0
where P0 is the initial population. (a) Compute lim tl ` Pstd. Explain why your answer is to be expected. (b) Compute lim Ml ` Pstd. (Note that A is defined in terms of M.) What kind of function is your result?
1 2 102r P− r 2 ln 10
M 2 P0
3 aax s2a 3x 2 x 4 2 a s 4 a2s ax 3
2
where is an experimentally determined constant, typically about 0.05. (a) What is the percentage of luminance sensed by a pupil of radius 3 mm? Use − 0.05. (b) Compute the percentage of luminance sensed by a pupil of radius 2 mm. Does it make sense that it is larger than the answer to part (a)? (c) Compute lim1 P. Is the result what you would expect?
as x approaches a, where a . 0. (At that time it was common to write aa instead of a 2.) Solve this problem. 86. T he figure shows a sector of a circle with central angle . Let Asd be the area of the segment between the chord PR and the arc PR. Let Bsd be the area of the triangle PQR. Find lim l 01 AsdyBsd. P A(¨)
rl0
Is this result physically possible? Source: Adapted from W. Stiles and B. Crawford, “The Luminous Efficiency of Rays Entering the Eye Pupil at Different Points.” Proceedings of the Royal Society of London, Series B: Biological Sciences 112 (1933): 428–50.
83. Logistic Equations Some populations initally grow exponentially but eventually level off. Equations of the form
O
87. Evaluate
M 1 1 Ae 2kt
where M, A, and k are positive constants, are called logistic equations and are often used to model such populations. (We will investigate these in detail in Chapter 9.) Here M is called
F
B(¨ ) R
Q
S DG
lim x 2 x 2 ln
xl`
Pstd −
¨
11x x
88. Suppose f is a positive function. If lim xl a f sxd − 0 and lim xl a tsxd − `, show that lim f f sxdg tsxd − 0
xla
This shows that 0 ` is not an indeterminate form.
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WRITING PROJECT The Origins of l’Hospital’s Rule
89. Find functions f and t where lim f sxd − lim tsxd − ` and xl0
(a) lim
xl0
xl0
(b) Show that f has derivatives of all orders that are defined on R. [Hint: First show by induction that there is a polynomial pnsxd and a nonnegative integer k n such that f sndsxd − pnsxdf sxdyx k n for x ± 0.]
f sxd − 7 (b) lim f f sxd 2 tsxdg − 7 xl0 tsxd
90. For what values of a and b is the following equation true? lim
xl0
S
sin 2x b 1a1 2 x3 x
91. Let f sxd −
H
e21yx 0
2
D
; 92. Let f sxd −
−0
if x ± 0 if x − 0
(a) Use the definition of derivative to compute f 9s0d.
319
H  x 1
x
if x ± 0 if x − 0
(a) Show that f is continuous at 0. (b) Investigate graphically whether f is differentiable at 0 by zooming in several times toward the point s0, 1d on the graph of f . (c) Show that f is not differentiable at 0. How can you reconcile this fact with the appearance of the graphs in part (b)?
Thomas Fisher Rare Book Library
WRITING PROJECT THE ORIGINS OF L’HOSPITAL’S RULE
www.StewartCalculus.com The Internet is another source of information for this project. Click on History of Mathematics for a list of reliable websites.
L’Hospital’s Rule was first published in 1696 in the Marquis de l’Hospital’s calculus textbook Analyse des infiniment petits, but the rule was discovered in 1694 by the Swiss mathematician John (Johann) Bernoulli. The explanation is that these two mathematicians had entered into a curious business arrangement whereby the Marquis de l’Hospital bought the rights to Bernoulli’s mathematical discoveries. The details, including a translation of l’Hospital’s letter to Bernoulli proposing the arrangement, can be found in the book by Eves [1]. Write an essay on the historical and mathematical origins of l’Hospital’s Rule. Start by providing brief biographical details of both men (the dictionary edited by Gillispie [2] is a good source) and outline the business deal between them. Then give l’Hospital’s statement of his rule, which is found in Struik’s source book [4] and more briefly in the book of Katz [3]. Notice that l’Hospital and Bernoulli formulated the rule geometrically and gave the answer in terms of differentials. Compare their statement with the version of l’Hospital’s Rule given in Section 4.4 and show that the two statements are essentially the same. 1. Howard W. Eves, Mathematical Circles: Volume 1 (Washington, D.C.: Mathematical Association of America, 2003). First published 1969 as In Mathematical Circles (Volume 2: Quadrants III and IV) by Prindle Weber and Schmidt. 2. C. C. Gillispie, ed., Dictionary of Scientific Biography, 8 vols. (New York: Scribner, 1981). See the article on Johann Bernoulli by E. A. Fellmann and J. O. Fleckstein in Volume II and the article on the Marquis de l’Hospital by Abraham Robinson in Volume III. 3. Victor J. Katz, A History of Mathematics: An Introduction. 3rd ed. (New York: Pearson, 2018). 4. Dirk Jan Stuik, ed. A Source Book in Mathematics, 1200 –1800 (1969; repr., Princeton, NJ: Princeton University Press, 2016).
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320
CHAPTER 4 Applications of Differentiation
4.5 Summary of Curve Sketching
30
y=8˛21≈+18x+2
_2
4 _10
FIGURE 1 8
0
y=8˛21≈+18x+2 6
2
FIGURE 2
So far we have been concerned with some particular aspects of curve sketching: domain, range, and symmetry in Chapter 1; limits, continuity, and asymptotes in Chapter 2; derivatives and tangents in Chapters 2 and 3; and extreme values, intervals of increase and decrease, concavity, points of inflection, and l’Hospital’s Rule in this chapter. It is now time to put all of this information together to sketch graphs that reveal the important features of functions. You might ask: Why don’t we just use a graphing calculator or computer to graph a curve? Why do we need to use calculus? It’s true that technology is capable of producing very accurate graphs. But even the best graphing devices have to be used intelligently. It is easy to arrive at a misleading graph, or to miss important details of a curve, when relying solely on technology. (See the topic Graphing Calculators and Computers at www.StewartCalculus.com, especially Examples 1, 3, 4, and 5. See also Section 4.6.) The use of calculus enables us to discover the most interesting aspects of graphs and in many cases to calculate maximum and minimum points and inflection points exactly instead of approximately. For instance, Figure 1 shows the graph of f sxd − 8x 3 2 21x 2 1 18x 1 2. At first glance it seems reasonable: It has the same shape as cubic curves like y − x 3, and it appears to have no maximum or minimum point. But if you compute the derivative, you will see that there is a maximum when x − 0.75 and a minimum when x − 1. Indeed, if we zoom in to this portion of the graph, we see that behavior exhibited in Figure 2. Without calculus, we could easily have overlooked it. In the next section we will graph functions by using the interaction between calculus and technology. In this section we draw graphs (by hand) by first considering the following information. A graph produced by a calculator or computer can serve as a check on your work.
■ Guidelines for Sketching a Curve The following checklist is intended as a guide to sketching a curve y − f sxd by hand. Not every item is relevant to every function. (For instance, a given curve might not have an asymptote or possess symmetry.) But the guidelines provide all the information you need to make a sketch that displays the most important aspects of the function. A. Domain It’s often useful to start by determining the domain D of f , that is, the set of values of x for which f sxd is defined.
y
0
x
(a) Even function: reflectional symmetry y
0
(b) Odd function: rotational symmetry
FIGURE 3
x
B. Intercepts The yintercept is f s0d and this tells us where the curve intersects the yaxis. To find the xintercepts, we set y − 0 and solve for x. (You can omit this step if the equation is difficult to solve.) C. Symmetry (i) If f s2xd − f sxd for all x in D, that is, the equation of the curve is unchanged when x is replaced by 2x, then f is an even function and the curve is symmetric about the yaxis. (See Section 1.1.) This means that our work is cut in half. If we know what the curve looks like for x > 0, then we need only reflect about the yaxis to obtain the complete curve [see Figure 3(a)]. Here are some examples: y − x 2, y − x 4, y − x , and y − cos x. (ii) If f s2xd − 2f sxd for all x in D, then f is an odd function and the curve is symmetric about the origin. Again we can obtain the complete curve if we know what it looks like for x > 0. [Rotate 180° about the origin; see Figure 3(b).] Some simple examples of odd functions are y − x, y − x 3, y − 1yx, and y − sin x.
 
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321
SECTION 4.5 Summary of Curve Sketching
(iii) If f sx 1 pd − f sxd for all x in D, where p is a positive constant, then f is a periodic function and the smallest such number p is called the period. For instance, y − sin x has period 2 and y − tan x has period . If we know what the graph looks like in an interval of length p, then we can use translation to visualize the entire graph (see Figure 4). y
FIGURE 4 Periodic function: translational symmetry
ap
0
period p
a
a+p
x
a+2p
D. Asymptotes (i) Horizontal Asymptotes. Recall from Section 2.6 that if either lim x l ` f sxd − L or lim x l2 ` f sxd − L, then the line y − L is a horizontal asymptote of the curve y − f sxd. If it turns out that lim x l ` f sxd − ` (or 2`), then we do not have an asymptote to the right, but this fact is still useful information for sketching the curve. (ii) Vertical Asymptotes. Recall from Section 2.2 that the line x − a is a vertical asymptote if at least one of the following statements is true: 1
lim f sxd − `
x l a1
lim f sxd − 2`
x l a1
lim f sxd − `
x l a2
lim f sxd − 2`
x l a2
(For rational functions you can locate the vertical asymptotes by equating the denominator to 0 after canceling any common factors. But for other functions this method does not apply.) Furthermore, in sketching the curve it is useful to know exactly which of the statements in (1) is true. If f sad is not defined but a is an endpoint of the domain of f, then you should compute lim xl a f sxd or lim xl a f sxd, whether or not this limit is infinite. (iii) Slant Asymptotes. These are discussed at the end of this section. 2
1
E. Intervals of Increase or Decrease Use the I/D Test. Compute f 9sxd and find the intervals on which f 9sxd is positive ( f is increasing) and the intervals on which f 9sxd is negative ( f is decreasing). F. Local Maximum or Minimum Values Find the critical numbers of f [the numbers c where f 9scd − 0 or f 9scd does not exist]. Then use the First Derivative Test. If f 9 changes from positive to negative at a critical number c, then f scd is a local maximum. If f 9 changes from negative to positive at c, then f scd is a local minimum. Although it is usually preferable to use the First Derivative Test, you can use the Second Derivative Test if f 9scd − 0 and f 0scd ± 0. Then f 0scd . 0 implies that f scd is a local minimum, whereas f 0scd , 0 implies that f scd is a local maximum. G. Concavity and Points of Inflection Compute f 0sxd and use the Concavity Test. The curve is concave upward where f 0sxd . 0 and concave downward where f 0sxd , 0. Inflection points occur where the direction of concavity changes. H. Sketch the Curve Using the information in items A– G, draw the graph. Sketch the asymptotes as dashed lines. Plot the intercepts, maximum and minimum points, and inflection points. Then make the curve pass through these points, rising and falling according to E, with concavity according to G, and approaching the asymptotes.
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322
CHAPTER 4 Applications of Differentiation
If additional accuracy is desired near any point, you can compute the value of the derivative there. The tangent indicates the direction in which the curve proceeds.
EXAMPLE 1 Use the guidelines to sketch the curve y − A. Domain The domain is hx
x
2
2 1 ± 0j − hx
2x 2 . x 21 2
 x ± 61j − s2`, 21d ø s21, 1d ø s1, `d
B. Intercepts The x and yintercepts are both 0. C. Symmetry Since f s2xd − f sxd, the function f is even. The curve is symmetric about the yaxis. 2x 2 2 D. Asymptotes lim 2 − lim −2 x l6` x 2 1 x l6` 1 2 1yx 2
y
Therefore the line y − 2 is a horizontal asymptote (at both the left and right). Since the denominator is 0 when x − 61, we compute the following limits: lim1
x l1
y=2
2x 2 −` x2 2 1
lim2
2x 2 − 2` x 21
lim 2
2x 2 −` x2 2 1
x l1
2
0
x=_1
lim 1
x
x l 21
2x − 2` 2 x 21
x l 21
2
Therefore the lines x − 1 and x − 21 are vertical asymptotes. This information about limits and asymptotes enables us to draw the preliminary sketch in Figure 5, showing the parts of the curve near the asymptotes.
x=1
FIGURE 5 Preliminary sketch
E. Intervals of Increase or Decrease
We have shown the curve approaching its horizontal asymptote from above in Figure 5. This is confirmed by the intervals of increase and decrease.
f 9sxd −
sx 2 2 1ds4xd 2 2x 2 2x 24x − 2 sx 2 2 1d2 sx 2 1d2
Since f 9sxd . 0 when x , 0 sx ± 21d and f 9sxd , 0 when x . 0 sx ± 1d, f is increasing on s2`, 21d and s21, 0d and decreasing on s0, 1d and s1, `d. F. Local Maximum or Minimum Values The only critical number is x − 0. Since f 9 changes from positive to negative at 0, f s0d − 0 is a local maximum by the First Derivative Test.
y
G. Concavity and Points of Inflection f 0sxd −
y=2 0
x=_1
x
x=1
FIGURE 6 Finished sketch of y −
2x 2 x 21 2
sx 2 2 1d2 s24d 1 4x 2sx 2 2 1d2x 12x 2 1 4 − 2 2 4 sx 2 1d sx 2 1d3
Since 12x 2 1 4 . 0 for all x, we have
 
f 0sxd . 0 &? x 2 2 1 . 0 &? x . 1
 
and f 0sxd , 0 &? x , 1. Thus the curve is concave upward on the intervals s2`, 21d and s1, `d and concave downward on s21, 1d. It has no point of inflection because 1 and 21 are not in the domain of f. H. Sketch the Curve Using the information in E – G, we finish the sketch in Figure 6. n
EXAMPLE 2 Sketch the graph of f sxd − A. Domain The domain is hx
x2 sx 1 1
.
 x 1 1 . 0j − hx  x . 21j − s21, `d.
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SECTION 4.5 Summary of Curve Sketching
323
B. Intercepts The x and yintercepts are both 0. C. Symmetry None D. Asymptotes Since lim
xl`
x2 sx 1 1
−`
there is no horizontal asymptote. Since sx 1 1 l 0 as x l 211 and f sxd is always positive, we have lim 1
x l 21
x2 sx 1 1
−`
and so the line x − 21 is a vertical asymptote.
E. Intervals of Increase or Decrease f 9sxd −
3x 2 1 4x xs3x 1 4d sx 1 1 s2xd 2 x 2 1y( 2sx 1 1 ) − 3y2 − x11 2sx 1 1d 2sx 1 1d3y2
W e see that f 9sxd − 0 when x − 0 (notice that 243 is not in the domain of f ), so the only critical number is 0. Since f 9sxd , 0 when 21 , x , 0 and f 9sxd . 0 when x . 0, f is decreasing on s21, 0d and increasing on s0, `d.
F. Local Maximum or Minimum Values Since f 9s0d − 0 and f 9 changes from negative to positive at 0, f s0d − 0 is a local (and absolute) minimum by the First Derivative Test. y
G. Concavity and Points of Inflection f 0sxd − y=
x=_1
FIGURE 7
0
≈ œ„„„„ x+1 x
2sx 1 1d3y2s6x 1 4d 2 s3x 2 1 4xd3sx 1 1d1y2 3x 2 1 8x 1 8 − 4sx 1 1d3 4sx 1 1d5y2
N ote that the denominator is always positive. The numerator is the quadratic 3x 2 1 8x 1 8, which is always positive because its discriminant is b 2 2 4ac − 232, which is negative, and the coefficient of x 2 is positive. Thus f 0sxd . 0 for all x in the domain of f , which means that f is concave upward on s21, `d and there is no point of inflection.
H. Sketch the Curve The curve is sketched in Figure 7.
EXAMPLE 3 Sketch the graph of f sxd − xe x. A. Domain The domain is R. B. Intercepts The x and yintercepts are both 0. C. Symmetry None D. Asymptotes Because both x and e x become large as x l `, we have lim x l ` xe x − `. As x l 2`, however, e x l 0 and so we have an indeterminate product that requires the use of l’Hospital’s Rule: lim xe x − lim
x l2`
x l2`
x 1 − lim − lim s2e x d − 0 x l2` 2e2x x l2` e2x
Thus the xaxis is a horizontal asymptote.
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n
324
CHAPTER 4 Applications of Differentiation
E. Intervals of Increase or Decrease f 9sxd − xe x 1 e x − sx 1 1de x Since e x is always positive, we see that f 9sxd . 0 when x 1 1 . 0, and f 9sxd , 0 when x 1 1 , 0. So f is increasing on s21, `d and decreasing on s2`, 21d. y
y=x´
F. Local Maximum or Minimum Values Because f 9s21d − 0 and f 9 changes from negative to positive at x − 21, f s21d − 2e21 < 20.37 is a local (and absolute) minimum. G. Concavity and Points of Inflection
1 _2
_1 (_1, _1/e)
FIGURE 8
f 0sxd − sx 1 1de x 1 e x − sx 1 2de x x
Since f 0sxd . 0 if x . 22 and f 0sxd , 0 if x , 22, f is concave upward on s22, `d and concave downward on s2`, 22d. The inflection point is s22, 22e22 d < s22, 20.27d. H. Sketch the Curve We use this information to sketch the curve in Figure 8.
EXAMPLE 4 Sketch the graph of f sxd − A. Domain The domain is R.
n
cos x . 2 1 sin x
B. Intercepts The yintercept is f s0d − 12. The xintercepts occur when cos x − 0, that is, x − sy2d 1 n, where n is an integer. C. Symmetry f is neither even nor odd, but f sx 1 2d − f sxd for all x and so f is periodic and has period 2. Thus, in what follows, we need to consider only 0 < x < 2 and then extend the curve by translation in part H. D. Asymptotes None E. Intervals of Increase or Decrease f 9sxd −
s2 1 sin xds2sin xd 2 cos x scos xd 2 sin x 1 1 −2 2 s2 1 sin xd s2 1 sin xd 2
The denominator is always positive, so f 9sxd . 0 when 2 sin x 1 1 , 0 &? sin x , 221 &? 7y6 , x , 11y6. So f is increasing on s7y6, 11y6d and decreasing on s0, 7y6d and s11y6, 2d. F. Local Maximum or Minimum Values From part E and the First Derivative Test, we see that the local minimum value is f s7y6d − 21ys3 and the local maximum value is f s11y6d − 1ys3. G. Concavity and Points of Inflection If we use the Quotient Rule again and simplify, we get f 0sxd − 2
2 cos x s1 2 sin xd s2 1 sin xd 3
Because s2 1 sin xd 3 . 0 and 1 2 sin x > 0 for all x, we know that f 0sxd . 0 when cos x , 0, that is, y2 , x , 3y2. So f is concave upward on sy2, 3y2d and concave downward on s0, y2d and s3y2, 2d. The inflection points are sy2, 0d and s3y2, 0d.
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325
SECTION 4.5 Summary of Curve Sketching
H. Sketch the Curve The graph of the function restricted to 0 < x < 2 is shown in Figure 9. Then we extend it, using periodicity, to arrive at the graph in Figure 10. y
11π 1 6 , œ„3
”
1 2
π
π 2
y
’
3π 2
1 2
2π x
_π
2π
π
3π
x
1  ’ ” 7π 6 , œ„3
FIGURE 9
FIGURE 10
n
EXAMPLE 5 Sketch the graph of y − lns4 2 x 2 d. A. Domain The domain is hx
 42x
2
. 0j − hx
x
2
, 4j − hx
  x  , 2j − s22, 2d
B. Intercepts The yintercept is f s0d − ln 4. To find the xintercept we set y − lns4 2 x 2 d − 0 We know that ln 1 − 0, so we have 4 2 x 2 − 1 ? x 2 − 3 and therefore the xintercepts are 6s3. C . Symmetry Since f s2xd − f sxd, f is even and the curve is symmetric about the yaxis. D. Asymptotes We look for vertical asymptotes at the endpoints of the domain. Since 4 2 x 2 l 0 1 as x l 2 2 and also as x l 221, we have lim lns4 2 x 2 d − 2` lim 1 lns4 2 x 2 d − 2`
x l 22
x l 22
Thus the lines x − 2 and x − 22 are vertical asymptotes.
E . Intervals of Increase or Decrease f 9sxd − y
(0, ln 4)
x=_2
x=2
{_œ„3, 0}
0
{œ„3, 0}
x
y − lns4 2 x 2 d
S ince f 9sxd . 0 when 22 , x , 0 and f 9sxd , 0 when 0 , x , 2, f is increasing on s22, 0d and decreasing on s0, 2d.
F . Local Maximum or Minimum Values The only critical number is x − 0. Since f 9 changes from positive to negative at 0, f s0d − ln 4 is a local maximum by the First Derivative Test. G. Concavity and Points of Inflection f 0sxd −
FIGURE 11
22x 4 2 x2
s4 2 x 2 ds22d 1 2xs22xd 28 2 2x 2 − s4 2 x 2 d2 s4 2 x 2 d2
S ince f 0sxd , 0 for all x, the curve is concave downward on s22, 2d and has no inflection point.
H. S ketch the Curve Using this information, we sketch the curve in Figure 11.
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n
326
CHAPTER 4 Applications of Differentiation
y
■ Slant Asymptotes Some curves have asymptotes that are oblique, that is, neither horizontal nor vertical. If
y=ƒ
lim f f sxd 2 smx 1 bdg − 0
ƒ(mx+b)
xl`
y=mx+b 0
x
FIGURE 12
where m ± 0, then the line y − mx 1 b is called a slant asymptote because the ver tical distance between the curve y − f sxd and the line y − mx 1 b approaches 0, as in Figure 12. (A similar situation exists if we let x l 2`.) In the case of rational functions, slant asymptotes occur when the degree of the numerator is one more than the degree of the denominator. In such a case the equation of the slant asymptote can be found by long division as in the following example.
EXAMPLE 6 Sketch the graph of f sxd −
x3 . x2 1 1
A. Domain The domain is R. B. Intercepts The x and yintercepts are both 0. C. Symmetry Since f s2xd − 2f sxd, f is odd and its graph is symmetric about the origin. D. Asymptotes Since x 2 1 1 is never 0, there is no vertical asymptote. Since f sxd l ` as x l ` and f sxd l 2` as x l 2`, there is no horizontal asymptote. But long division gives f sxd −
This equation suggests that y − x is a candidate for a slant asymptote. In fact,
f sxd 2 x − 2
x3 x −x2 2 x 11 x 11 2
x −2 x2 1 1
1 x 1 11 2 x
l 0 as x l 6`
So the line y − x is indeed a slant asymptote.
E. Intervals of Increase or Decrease f 9sxd −
sx 2 1 1ds3x 2 d 2 x 3 2x x 2sx 2 1 3d − 2 2 sx 1 1d sx 2 1 1d2
Since f 9sxd . 0 for all x (except 0), f is increasing on s2`, `d.
F. Local Maximum or Minimum Values Although f 9s0d − 0, f 9 does not change sign at 0, so there is no local maximum or minimum. G. Concavity and Points of Inflection f 0sxd −
sx 2 1 1d2 s4x 3 1 6xd 2 sx 4 1 3x 2 d 2sx 2 1 1d2x 2xs3 2 x 2 d − sx 2 1 1d4 sx 2 1 1d3
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SECTION 4.5 Summary of Curve Sketching
y
y=
˛ ≈+1
Since f 0sxd − 0 when x − 0 or x − 6s3, we set up the following chart: Interval
”œ„3,
0
”_œ„3, _
3œ„ 3 ’ 4
x , 2s3 2s3 , x , 0
x
3œ„ 3 ’ 4
0 , x , s3 x . s3
inflection points
y=x
x
3 2 x2
sx 2 1 1d3
f 0sxd
f
2
2
1
1
CU on (2`, 2s3 )
2
1
1
2
1
1
1
1
1
2
1
2
CD on (2s3, 0) CU on ( 0, s3 ) CD on (s3, `)
The points of inflection are (2s3, 243 s3 ), s0, 0d, and (s3, 34 s3 ).
FIGURE 13
327
H. Sketch the Curve The graph of f is sketched in Figure 13.
n
4.5 Exercises 1–54 Use the guidelines of this section to sketch the curve. 3
2
3
1. y − x 1 3x
2. y − 2x 2 12x 1 18x
4
4
3. y − x 2 4x
5
5. y − xsx 2 4d 8 3 3x
7. y − 9. y −
2x 1 3 x12
2
2
4. y − x 2 8x 1 8 3
1 5 5x
2
1 16x
x 2 1 5x 25 2 x 2
12. y − 1 1
13. y −
x x2 2 4
14. y −
1 1 1 2 x x
1 x2 2 4
sx 2 1d2 16. y − 2 x 11 18. y −
x x 21 3
x3 19. y − 3 x 11
x3 20. y − x22
21. y − sx 2 3dsx
3 x 22. y − sx 2 4ds
23. y − sx 1 x 2 2
24. y − sx 1 x 2 x
25. y − 27. y −
x sx 1 1 2
s1 2 x 2 x 1y3
29. y − x 2 3x
35. y − x tan x, 2y2 , x , y2 37. y − sin x 1 s3 cos x, 22 < x < 2
x2x 2 2 3x 1 x 2
2
34. y − x 1 cos x
8. y − s4 2 x d
11. y −
x21 x2
33. y − sin3 x
36. y − 2x 2 tan x, 2y2 , x , y2
2 5
2
17. y −
3 x3 1 1 32. y − s
6. y − x 2 5x
10. y −
x2 15. y − 2 x 13
3 x 2 2 1 31. y − s
2
26. y − x s2 2 x 2 28. y −
x sx 2 1 2
30. y − x 5y3 2 5x 2y3
38. y − csc x 2 2sin x, 0 , x , 39. y −
sin x 1 1 cos x
41. y − arctanse x d
40. y −
sin x 2 1 cos x
42. y − s1 2 xde x
43. y − 1ys1 1 e 2x d 44. y − e2x sin x, 0 < x < 2 45. y −
1 1 ln x x
46. y − x sln xd 2
47. y − s1 1 e x d22
48. y − e xyx 2
49. y − lnssin xd
50. y − lns1 1 x 3d
51. y − xe21yx
52. y −
53. y − e arctan x
54. y − tan21
ln x x2
S D x21 x11
55–58 The graph of a function f is shown. (The dashed lines indicate horizontal asymptotes.) Find each of the following for the given function t. (a) The domains of t and t9 (b) The critical numbers of t (c) The approximate value of t9s6d
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328
CHAPTER 4 Applications of Differentiation
(d) All vertical and horizontal asymptotes of t
section of the beam.) Sketch the graph of the deflection curve.
y
y
W
f 0
L
1 0
x
1
55. tsxd − s f sxd

3 f sxd 56. tsxd − s

57. tsxd − f sxd
58. tsxd − 1yf sxd
59. In the theory of relativity, the mass of a particle is m−
64. C oulomb’s Law states that the force of attraction between two charged particles is directly proportional to the product of the charges and inversely proportional to the square of the distance between them. The figure shows particles with charge 1 located at positions 0 and 2 on a coordinate line and a particle with charge 21 at a position x between them. It follows from Coulomb’s Law that the net force acting on the middle particle is
m0
Fsxd − 2
s1 2 v 2yc 2
where m 0 is the rest mass of the particle, m is the mass when the particle moves with speed v relative to the observer, and c is the speed of light. Sketch the graph of m as a function of v. E − sm 02 c 4 1 h 2 c 2y2
61. A model for the spread of a rumor is given by the equation pstd −
1 1 1 ae2kt
where pstd is the proportion of the population that knows the rumor at time t and a and k are positive constants. (a) When will half the population have heard the rumor? (b) When is the rate of spread of the rumor greatest? (c) Sketch the graph of p.
62. A model for the concentration at time t of a drug injected into the bloodstream is Cstd − Kse
2at
2e
2bt
d
where a, b, and K are positive constants and b . a. Sketch the graph of the concentration function. What does the graph tell us about how the concentration varies as time passes? 63. T he figure shows a beam of length L embedded in concrete walls. If a constant load W is distributed evenly along its length, the beam takes the shape of the deflection curve W 4 WL 3 WL 2 2 x 1 x 2 x y−2 24EI 12EI 24EI where E and I are positive constants. (E is Young’s modulus of elasticity and I is the moment of inertia of a cross
0,x,2
where k is a positive constant. Sketch the graph of the net force function. What does the graph say about the force?
60. In the theory of relativity, the energy of a particle is
where m 0 is the rest mass of the particle, is its wave length, and h is Planck’s constant. Sketch the graph of E as a function of . What does the graph say about the energy?
k k 1 x2 sx 2 2d2
+1
_1
+1
0
x
2
x
65–68 Find an equation of the slant asymptote. Do not sketch the curve. 65. y −
x2 1 1 x11
66. y −
4x 3 2 10x 2 2 11x 1 1 x 2 2 3x
67. y −
2x 3 2 5x 2 1 3x x2 2 x 2 2
68. y −
26x 4 1 2x 3 1 3 2x 3 2 x
69–74 Use the guidelines of this section to sketch the curve. In guideline D, find an equation of the slant asymptote. 69. y −
x2 x21
70. y −
1 1 5x 2 2x 2 x22
71. y −
x3 1 4 x2
72. y −
x3 sx 1 1d2
73. y − 1 1 12 x 1 e2x
74. y − 1 2 x 1 e 11xy3
75. S how that the curve y − x 2 tan21x has two slant asymptotes: y − x 1 y2 and y − x 2 y2. Use this fact to help sketch the curve. 76. S how that the curve y − sx 2 1 4x has two slant asymptotes: y − x 1 2 and y − 2x 2 2. Use this fact to help sketch the curve. 77. S how that the lines y − sbyadx and y − 2sbyadx are slant asymptotes of the hyperbola sx 2ya 2 d 2 s y 2yb 2 d − 1.
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SECTION 4.6 Graphing with Calculus and Technology
329
79. D iscuss the asymptotic behavior of f sxd − sx 4 1 1dyx in the same manner as in Exercise 78. Then use your results to help sketch the graph of f .
78. Let f sxd − sx 3 1 1dyx. Show that lim f f sxd 2 x 2 g − 0
x l 6`
This shows that the graph of f approaches the graph of y − x 2, and we say that the curve y − f sxd is asymptotic to the parabola y − x 2. Use this fact to help sketch the graph of f .
80. U se the asymptotic behavior of f sxd − sin x 1 e2x to sketch its graph without going through the curvesketching procedure of this section.
4.6 Graphing with Calculus and Technology You may want to read Graphing Calculators and Computers at www.StewartCalculus.com if you haven’t already. In particular, it explains how to avoid some of the pitfalls of graphing devices by choosing appropriate viewing rectangles.
The method we used to sketch curves in the preceding section was a culmination of much of our study of differential calculus. The graph was the final object that we produced. In this section our point of view is completely different. Here we start with a graph produced by a graphing calculator or computer and then we refine it. We use calculus to make sure that we reveal all the important aspects of the curve. And with the use of graphing devices we can tackle curves that would be far too complicated to consider without technology. The theme is the interaction between calculus and technology.
EXAMPLE 1 Graph the polynomial f sxd − 2x 6 1 3x 5 1 3x 3 2 2x 2. Use the graphs of f 9 and f 0 to estimate all maximum and minimum points and intervals of concavity.
41,000
y=ƒ _5
_1000
5
FIGURE 1 100 y=ƒ
f 9sxd − 12x 5 1 15x 4 1 9x 2 2 4x
_3
f 0sxd − 60x 4 1 60x 3 1 18x 2 4
2
_50
FIGURE 2
SOLUTION If we specify a domain but not a range, graphing software will often deduce a suitable range from the values computed. Figure 1 shows a plot that may result if we specify that 25 < x < 5. Although this viewing rectangle is useful for showing that the asymptotic behavior (or end behavior) is the same as for y − 2x 6, it is obviously hiding some finer detail. So we change to the viewing rectangle f23, 2g by f250, 100g in Figure 2. Most graphing calculators and graphing software allow us to “trace” along a curve and see approximate coordinates of points. (Some also have features to identify the approximate locations of local maximum and minimum points.) Here it appears that there is an absolute minimum value of about 215.33 when x < 21.62 and f is decreasing on s2`, 21.62d and increasing on s21.62, `d. Also, there appears to be a horizontal tangent at the origin and inflection points when x − 0 and when x is somewhere between 22 and 21. Now let’s try to confirm these impressions using calculus. We differentiate and get
When we graph f 9 in Figure 3 we see that f 9sxd changes from negative to positive when x < 21.62; this confirms (by the First Derivative Test) the minimum value that we found earlier. But, perhaps to our surprise, we also notice that f 9sxd changes from positive to negative when x − 0 and from negative to positive when x < 0.35. This means that f has a local maximum at 0 and a local minimum when x < 0.35, but these were hidden in Figure 2. Indeed, if we now zoom in toward the origin in Figure 4, we 1
20
y=ƒ
y=fª(x)
_1 _3
2
_1
_5
FIGURE 3
1
FIGURE 4
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330
CHAPTER 4 Applications of Differentiation
see what we missed before: a local maximum value of 0 when x − 0 and a local minimum value of about 20.1 when x < 0.35. What about concavity and inflection points? From Figures 2 and 4 there appear to be inflection points when x is a little to the left of 21 and when x is a little to the right of 0. But it’s difficult to determine inflection points from the graph of f , so we graph the second derivative f 0 in Figure 5. We see that f 0 changes from positive to negative when x < 21.23 and from negative to positive when x < 0.19. So, correct to two decimal places, f is concave upward on s2`, 21.23d and s0.19, `d and concave downward on s21.23, 0.19d. The inflection points are s21.23, 210.18d and s0.19, 20.05d. We have discovered that no single graph reveals all the important features of this polynomial. But Figures 2 and 4, when taken together, do provide an accurate picture. n
10 _3
2 y=f·(x)
_30
FIGURE 5
EXAMPLE 2 Draw the graph of the function f sxd −
x 2 1 7x 1 3 x2
in a viewing rectangle that shows all the important features of the function. Estimate the local maximum and minimum values and the intervals of concavity. Then use calculus to find these quantities exactly. SOLUTION Figure 6 — produced by graphing software with automatic scaling—is a disaster. Some graphing calculators use f210, 10g by f210, 10g as the default viewing rectangle, so let’s try it. We get the graph shown in Figure 7; it’s a major improvement. 3 10!*
10 y=ƒ _10
y=ƒ _5
10
5
FIGURE 6
_10
FIGURE 7
The yaxis appears to be a vertical asymptote and indeed it is because lim
xl0
10 y=ƒ y=1 20
_20 _5
FIGURE 8
x 2 1 7x 1 3 −` x2
Figure 7 also allows us to estimate the xintercepts: about 20.5 and 26.5. The exact values are obtained by using the quadratic formula to solve the equation x 2 1 7x 1 3 − 0; we get x − (27 6 s37 )y2. To get a better look at horizontal asymptotes, we change to the viewing rectangle f220, 20g by f25, 10g in Figure 8. It appears that y − 1 is the horizontal asymptote and this is easily confirmed: lim
x l 6`
S
x 2 1 7x 1 3 7 3 − lim 1 1 1 2 2 x l 6` x x x
D
−1
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SECTION 4.6 Graphing with Calculus and Technology 2 _3
0
To estimate the minimum value we zoom in to the viewing rectangle f23, 0g by f24, 2g in Figure 9. We find that the absolute minimum value is about 23.1 when x < 20.9, and we see that the function decreases on s2`, 20.9d and s0, `d and increases on s20.9, 0d. The exact values are obtained by differentiating:
y=ƒ
f 9sxd − 2 _4
7 6 7x 1 6 2 3 −2 x2 x x3
This shows that f 9sxd . 0 when 267 , x , 0 and f 9sxd , 0 when x , 267 and when 37 < 23.08. x . 0. The exact minimum value is f (2 67 ) − 2 12 Figure 9 also shows that an inflection point occurs somewhere between x − 21 and x − 22. We could estimate it much more accurately using the graph of the second derivative, but in this case it’s just as easy to find exact values. Since
FIGURE 9
f 0sxd −
14 18 2s7x 1 9d 3 1 4 − x x x4
we see that f 0sxd . 0 when x . 297 sx ± 0d and f 0sxd , 0 when x , 297. So f is concave upward on (297 , 0) and s0, `d and concave downward on (2`, 297 ). The inflection point is (297 , 271 27 ). The analysis using the first two derivatives shows that Figure 8 displays all the major aspects of the curve.
EXAMPLE 3 Graph the function f sxd − 10
_10
y=ƒ
331
10
x 2sx 1 1d3 . sx 2 2d2sx 2 4d4
SOLUTION Drawing on our experience with a rational function in Example 2, let’s start by graphing f in the viewing rectangle f210, 10g by f210, 10g. From Figure 10 we have the feeling that we are going to have to zoom in to see some finer detail and also zoom out to see the larger picture. But, as a guide to intelligent zooming, let’s first take a close look at the expression for f sxd. Because of the factors sx 2 2d2 and sx 2 4d4 in the denominator, we expect x − 2 and x − 4 to be the vertical asymptotes. Indeed
_10
lim
FIGURE 10
n
x l2
x 2sx 1 1d3 x 2sx 1 1d3 − ` and lim −` x l 4 sx 2 2d2sx 2 4d4 sx 2 2d2sx 2 4d4
To find the horizontal asymptotes, we divide numerator and denominator by x 6: x 2 sx 1 1d3 x 2sx 1 1d3 x3 x3 − − 2 4 2 sx 2 2d sx 2 4d sx 2 2d sx 2 4d4 x2 x4
y
_1
FIGURE 11
1
2
3
4
x
S D S DS D 1 1 11 x x
12
2 x
2
12
3
4 x
4
This shows that f sxd l 0 as x l 6`, so the xaxis is a horizontal asymptote. It is also very useful to consider the behavior of the graph near the xintercepts using an analysis like that in Example 2.6.12. Since x 2 is positive, f sxd does not change sign at 0 and so its graph doesn’t cross the xaxis at 0. But, because of the factor sx 1 1d3, the graph does cross the xaxis at 21 and has a horizontal tangent there. Putting all this information together, but without using derivatives, we see that the curve has to look something like the one in Figure 11.
Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
332
CHAPTER 4 Applications of Differentiation
Now that we know what to look for, we zoom in (several times) to produce the graphs in Figures 12 and 13 and zoom out (several times) to get Figure 14. 0.05
0.0001
500 y=ƒ
y=ƒ _100
1
_1.5
0.5
y=ƒ _0.05
_0.0001
FIGURE 12
FIGURE 13
_1
_10
10
FIGURE 14
We can read from these graphs that the absolute minimum is about 20.02 and occurs when x < 220. There is also a local maximum 0, we have T9sxd − 0 &? T
1
4
x
6
−
1 &? 4x − 3sx 2 1 9 8
&? 16x 2 − 9sx 2 1 9d &? 7x 2 − 81 &? x −
Ts0d − 1.5 T 2
6 sx 1 9 2
9 s7
The only critical number is x − 9ys7 . To see whether the minimum occurs at this critical number or at an endpoint of the domain f0, 8g, we follow the Closed Interval Method by evaluating T at all three points:
y=T(x)
0
x
FIGURE 8
y
S D 9
s7
−11
s7 s73 < 1.33 Ts8d − < 1.42 8 6
Since the smallest of these values of T occurs when x − 9ys7 , the absolute minimum value of T must occur there. Figure 8 illustrates this calculation by showing the graph of T. Thus the woman should land the boat at a point 9ys7 km ( 0). This value of x gives a maximum value of A since As0d − 0 and Asrd − 0. Therefore the area of the largest inscribed rectangle is
S D
A
r
s2
−2
r s2
Î
r2 2
r2 − r2 2
SOLUTION 2 A simpler solution is possible if we think of using an angle as a variable. Let be the angle shown in Figure 10. Then the area of the rectangle is r ¨
r cos ¨
FIGURE 10
r sin ¨
Asd − s2r cos dsr sin d − r 2s2 sin cos d − r 2 sin 2 We know that sin 2 has a maximum value of 1 and it occurs when 2 − y2. So Asd has a maximum value of r 2 and it occurs when − y4. Notice that this trigonometric solution doesn’t involve differentiation. In fact, we didn’t need to use calculus at all. n
■ Applications to Business and Economics In Section 3.7 we introduced the idea of marginal cost. Recall that if Csxd, the cost function, is the cost of producing x units of a certain product, then the marginal cost is the rate of change of C with respect to x. In other words, the marginal cost function is the derivative, C9sxd, of the cost function. Now let’s consider marketing. Let psxd be the price per unit that the company can charge if it sells x units. Then p is called the demand function (or price function) and we would expect it to be a decreasing function of x. (More units sold corresponds to a lower price.) If x units are sold and the price per unit is psxd, then the total revenue is Rsxd − quantity 3 price − xpsxd and R is called the revenue function. The derivative R9 of the revenue function is called the marginal revenue function and it is the rate of change of revenue with respect to the number of units sold. If x units are sold, then the total profit is Psxd − Rsxd 2 Csxd and P is called the profit function. The marginal profit function is P9, the derivative of the profit function. In Exercises 65 – 69 you are asked to use the marginal cost, revenue, and profit functions to minimize costs and maximize revenues and profits.
EXAMPLE 6 A store has been selling 200 TV monitors a week at $350 each. A market survey indicates that for each $10 rebate offered to buyers, the number of monitors sold will increase by 20 a week. Find the demand function and the revenue function. How large a rebate should the store offer to maximize revenue? SOLUTION If x is the number of monitors sold per week, then the weekly increase in sales is x 2 200. For each increase of 20 units sold, the price is decreased by $10. So Copyright 2021 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
342
CHAPTER 4 Applications of Differentiation 1 for each additional unit sold, the decrease in price will be 20 3 10 and the demand function is 1 psxd − 350 2 10 20 sx 2 200d − 450 2 2 x
The revenue function is
Rsxd − xpsxd − 450x 2 12 x 2
Since R9sxd − 450 2 x, we see that R9sxd − 0 when x − 450. This value of x gives an absolute maximum by the First Derivative Test (or simply by observing that the graph of R is a parabola that opens downward). The corresponding price is ps450d − 450 2 12 s450d − 225 and the rebate is 350 2 225 − 125. Therefore, to maximize revenue, the store should offer a rebate of $125. n
4.7 Exercises 1. Consider the following problem: find two numbers whose sum is 23 and whose product is a maximum. (a) Make a table of values, like the one below, so that the sum of the numbers in the first two columns is always 23. On the basis of the evidence in your table, estimate the answer to the problem. (b) Use calculus to solve the problem and compare with your answer to part (a). First number
Second number
Product