Business analytics: methods, models, and decisions [Internat. ed] 9780132950619, 0132950618, 9780133051711, 0133051714

A balanced, holistic approach to understanding business analytics. This book provides readers with the fundamental conce

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English Pages 650 Seiten: Illustrationen [686] Year 2012;2014

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Business analytics: methods, models, and decisions [Internat. ed]
 9780132950619, 0132950618, 9780133051711, 0133051714

Table of contents :
Cover......Page 1
Title Page......Page 2
Copyright Page......Page 3
Acknowledgements......Page 18
Contents......Page 6
Preface......Page 14
About the Author......Page 20
Learning Objectives......Page 22
What Is Business Analytics?......Page 24
Evolution of Business Analytics......Page 26
Scope of Business Analytics......Page 27
Data for Business Analytics......Page 29
Decision Models......Page 34
Problem Solving and Decision Making......Page 43
Problems and Exercises......Page 46
Case: Performance Lawn Equipment......Page 49
Learning Objectives......Page 52
Basic Excel Skills......Page 54
Excel Functions......Page 58
Spreadsheet Add-Ins for Business Analytics......Page 64
Spreadsheet Modeling and Spreadsheet Engineering......Page 65
Problems and Exercises......Page 70
Case: Performance Lawn Equipment......Page 72
Learning Objectives......Page 74
Data Visualization......Page 75
Data Queries: Using Sorting and Filtering......Page 81
Statistical Methods for Summarizing Data......Page 86
Exploring Data Using PivotTables......Page 98
Key Terms......Page 102
Problems and Exercises......Page 103
Case: Performance Lawn Equipment......Page 105
Learning Objectives......Page 106
Populations and Samples......Page 107
Measures of Location......Page 108
Measures of Dispersion......Page 112
Measures of Shape......Page 120
Excel Descriptive Statistics Tool......Page 123
Descriptive Statistics for Grouped Data......Page 124
Measures of Association......Page 127
Outliers......Page 134
Statistical Thinking in Business Decisions......Page 136
Problems and Exercises......Page 140
Case: Performance Lawn Equipment......Page 145
Learning Objectives......Page 146
Basic Concepts of Probability......Page 147
Random Variables and Probability Distributions......Page 153
Discrete Probability Distributions......Page 156
Continuous Probability Distributions......Page 164
Random Sampling from Probability Distributions......Page 176
Data Modeling and Distribution Fitting......Page 183
Key Terms......Page 187
Problems and Exercises......Page 188
Case: Performance Lawn Equipment......Page 195
Learning Objectives......Page 196
Statistical Sampling......Page 197
Estimating Population Parameters......Page 201
Sampling Error......Page 202
Sampling Distributions......Page 204
Interval Estimates......Page 206
Confidence Intervals......Page 207
Prediction Intervals......Page 213
Confidence Intervals and Sample Size......Page 214
Problems and Exercises......Page 216
Case: Performance Lawn Equipment......Page 219
Learning Objectives......Page 220
Hypothesis Testing......Page 221
One-Sample Hypothesis Tests......Page 222
Two-Sample Hypothesis Tests......Page 229
Analysis of Variance......Page 236
Chi-Square Test for Independence......Page 238
Problems and Exercises......Page 242
Case: Performance Lawn Equipment......Page 246
Learning Objectives......Page 247
Logic-Driven Modeling......Page 248
Data-Driven Modeling......Page 257
Analyzing Uncertainty and Model Assumptions......Page 264
Model Analysis Using Risk Solver Platform......Page 272
Problems and Exercises......Page 277
Case: Performance Lawn Equipment......Page 281
Learning Objectives......Page 282
Simple Linear Regression......Page 283
Residual Analysis and Regression Assumptions......Page 292
Multiple Linear Regression......Page 295
Building Good Regression Models......Page 300
Regression with Categorical Independent Variables......Page 304
Regression Models with Nonlinear Terms......Page 308
Problems and Exercises......Page 312
Case: Performance Lawn Equipment......Page 316
Learning Objectives......Page 318
Qualitative and Judgmental Forecasting......Page 319
Statistical Forecasting Models......Page 321
Forecasting Models for Time Series with a Linear Trend......Page 332
Forecasting Time Series with Seasonality......Page 336
Selecting Appropriate Time-Series-Based Forecasting Models......Page 343
Regression Forecasting with Causal Variables......Page 344
The Practice of Forecasting......Page 346
Problems and Exercises......Page 347
Case: Performance Lawn Equipment......Page 349
Learning Objectives......Page 350
Spreadsheet Models with Random Variables......Page 352
Monte Carlo Simulation Using Risk Solver Platform......Page 354
New-Product Development Model......Page 360
Newsvendor Model......Page 368
Overbooking Model......Page 372
Cash Budget Model......Page 373
Problems and Exercises......Page 381
Case: Performance Lawn Equipment......Page 386
Learning Objectives......Page 387
The Scope of Data Mining......Page 389
Data Exploration and Reduction......Page 390
Classification......Page 393
Classification Techniques......Page 402
Association Rule Mining......Page 414
Cause-and-Effect Modeling......Page 418
Problems and Exercises......Page 422
Case: Performance Lawn Equipment......Page 423
Learning Objectives......Page 425
Building Linear Optimization Models......Page 426
Implementing Linear Optimization Models on Spreadsheets......Page 430
Solving Linear Optimization Models......Page 432
Graphical Interpretation of Linear Optimization......Page 439
How Solver Works......Page 444
Solver Outcomes and Solution Messages......Page 446
Using Optimization Models for Prediction and Insight......Page 450
Problems and Exercises......Page 460
Case: Performance Lawn Equipment......Page 466
Learning Objectives......Page 467
Types of Constraints in Optimization Models......Page 469
Process Selection Models......Page 470
Blending Models......Page 474
Portfolio Investment Models......Page 478
Transportation Models......Page 482
Multiperiod Production Planning Models......Page 486
Multiperiod Financial Planning Models......Page 489
Models with Bounded Variables......Page 494
A Production/Marketing Allocation Model......Page 499
Key Terms......Page 504
Problems and Exercises......Page 505
Case: Performance Lawn Equipment......Page 517
Learning Objectives......Page 519
Solving Models with General Integer Variables......Page 520
Integer Optimization Models with Binary Variables......Page 529
Mixed-Integer Optimization Models......Page 539
Key Terms......Page 544
Problems and Exercises......Page 545
Case: Performance Lawn Equipment......Page 552
Learning Objectives......Page 554
Modeling and Solving Nonlinear Optimization Problems......Page 555
Quadratic Optimization......Page 569
Evolutionary Solver for Non-Smooth Optimization......Page 573
Problems and Exercises......Page 582
Case: Performance Lawn Equipment......Page 587
Learning Objectives......Page 588
Risk Analysis in Optimization......Page 589
Optimizing Monte Carlo Simulation Models......Page 600
Simulation Optimization Using Risk Solver Platform......Page 602
Problems and Exercises......Page 608
Case: Performance Lawn Equipment......Page 611
Learning Objectives......Page 612
Making Decisions with Uncertain Information......Page 613
Decision Trees......Page 619
The Value of Information......Page 627
Utility and Decision Making......Page 630
Problems and Exercises......Page 637
Case: Performance Lawn Equipment......Page 643
Appendix A......Page 646
Appendix B......Page 650
C......Page 674
E......Page 675
L......Page 676
P......Page 677
S......Page 678
Z......Page 679
C......Page 680
E......Page 681
K......Page 682
N......Page 683
R......Page 684
S......Page 685
Z......Page 686

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