Applications of Hypothesis Testing for Environmental Science 0128243015, 9780128243015

Applications of Hypothesis Testing for Environmental Science presents the theory and application of hypothesis testing i

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Applications of Hypothesis Testing for Environmental Science
 0128243015, 9780128243015

Table of contents :
Applications of Hypothesis Testing for Environmental Science
Copyright
Dedication
Contents
Preface
1 Introduction to statistical hypothesis testing
Learning outcomes
1.1 Introduction
1.2 What is hypothesis testing?
1.3 The general procedure for performing statistical hypothesis testing
1.4 Procedures for performing hypothesis testing
1.5 Types of errors
Further reading
2 Z-test for one-sample mean
Learning outcomes
2.1 Introduction
2.2 What is normal distribution?
2.3 What is standard normal distribution?
2.4 Finding the area under the normal curve
2.5 Hypothesis testing for one sample mean (Z-test)
Further reading
3 t-test for one-sample mean
Learning outcomes
3.1 Introduction
3.2 What is t distribution?
3.3 Finding the t critical values
3.4 Hypothesis testing for a one-sample mean (t-test)
Further reading
4 Z-test for one sample proportion
Learning outcomes
4.1 Introduction
4.2 What is Bernoulli distribution?
4.3 What is Binomial distribution?
4.4 Hypothesis testing for one sample proportion (Z-test)
Further reading
5 Chi-square test for one sample variance
Learning outcomes
5.1 Introduction
5.2 What is chi-square distribution?
5.3 Finding the chi-square values (area under the chi-square curve)
5.4 Hypothesis testing for one-sample variance or standard deviation
Further reading
6 The observed significance level (P-value) procedure
Learning outcomes
6.1 Introduction
6.2 What is the observed significance level?
6.3 Computing the P-value for a Z-test
6.4 Testing one sample mean when the variance is known: P-value
6.5 Computing the P-value for a t-test
6.6 Testing one sample mean when the variance is unknown: P-value
6.7 Testing one sample proportion: P-value
6.8 Compute the P-value for a chi-square test
6.9 Testing one-sample population variance or standard deviation: P-value
Further reading
7 Interval estimation for one population
Learning outcomes
7.1 Introduction
7.2 What is interval estimation?
7.3 Confidence interval for one population mean
7.3.1 When the sample size is large
7.3.2 When the sample size is small
7.4 Confidence interval for one population proportion
7.5 Confidence interval for one population variance
Further reading
8 The interval estimation procedure: hypothesis testing for one population
Learning outcomes
8.1 Introduction
8.2 The steps for the confidence interval procedure
8.3 Confidence interval for testing one mean value: Z-test
8.4 Confidence interval for testing one mean value: t-test
8.5 Confidence interval for testing one proportion value
8.6 Confidence interval for testing one standard deviation value
Further reading
9 Hypothesis testing for the difference between two populations
Learning outcomes
9.1 Introduction
9.2 The general procedure for testing two samples
9.3 Testing the difference between two means when the sample size is large
9.4 Testing the difference between two means when the sample size is small
9.5 Testing two dependent samples
9.6 Testing the difference between two proportions
9.7 Testing the ratio of two variances
Further reading
10 Interval estimation for the difference between two populations
Learning outcomes
10.1 Introduction
10.2 The steps for the confidence interval procedure for the difference between two populations
10.3 Confidence interval for the difference between two means when the sample size is large
10.4 Confidence interval for the difference between two means when the sample size is small
10.5 Confidence interval for dependent samples
10.6 Confidence interval for the difference between two proportions
10.7 Confidence interval for the ratio of two variances
Further reading
11 The interval estimation procedure: hypothesis testing for two populations
Learning outcomes
11.1 Introduction
11.2 The steps for the confidence interval procedure for the difference between two populations
11.3 Confidence interval for testing the difference between two means when sample size is large
11.4 Confidence interval for testing the difference between two means when the sample size is small
11.5 Confidence interval for testing two dependent samples
11.6 Confidence interval for testing the difference between two proportions
11.7 Confidence interval for testing the ratio of two variances
Further reading
Appendix
Index

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