Applications of Hypothesis Testing for Environmental Science

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