Read more
"...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." -CHOICE
This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes:
* New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power
* SPSS(r) (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures
* Data sets and odd-numbered solutions provided in an appendix, and tables of critical values
* Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.
List of contents
PREFACE ix
LIST OF VARIABLES xiii
CHAPTER 1 NONPARAMETRIC STATISTICS: AN INTRODUCTION 1
1.1 Objectives 1
1.2 Introduction 1
1.3 The Nonparametric Statistical Procedures Presented in This Book 3
1.3.1 State the Null and Research Hypotheses 4
1.3.2 Set the Level of Risk (or the Level of Signifi cance) Associated with the Null Hypothesis 4
1.3.3 Choose the Appropriate Test Statistic 5
1.3.4 Compute the Test Statistic 5
1.3.5 Determine the Value Needed for Rejection of the Null Hypothesis Using the Appropriate Table of Critical Values for the Particular Statistic 5
1.3.6 Compare the Obtained Value with the Critical Value 6
1.3.7 Interpret the Results 6
1.3.8 Reporting the Results 6
1.4 Ranking Data 6
1.5 Ranking Data with Tied Values 7
1.6 Counts of Observations 8
1.7 Summary 9
1.8 Practice Questions 9
1.9 Solutions to Practice Questions 10
CHAPTER 2 TESTING DATA FOR NORMALITY 13
2.1 Objectives 13
2.2 Introduction 13
2.3 Describing Data and the Normal Distribution 14
2.4 Computing and Testing Kurtosis and Skewness for Sample Normality 17
2.4.1 Sample Problem for Examining Kurtosis 19
2.4.2 Sample Problem for Examining Skewness 22
2.4.3 Examining Skewness and Kurtosis for Normality Using SPSS 24
2.5 Computing the Kolmogorov-Smirnov One-Sample Test 27
2.5.1 Sample Kolmogorov-Smirnov One-Sample Test 29
2.5.2 Performing the Kolmogorov-Smirnov One-Sample Test Using SPSS 34
2.6 Summary 37
2.7 Practice Questions 37
2.8 Solutions to Practice Questions 38
CHAPTER 3 COMPARING TWO RELATED SAMPLES: THE WILCOXON SIGNED RANK AND THE SIGN TEST 39
3.1 Objectives 39
3.2 Introduction 39
3.3 Computing the Wilcoxon Signed Rank Test Statistic 40
3.3.1 Sample Wilcoxon Signed Rank Test (Small Data Samples) 41
3.3.2 Confi dence Interval for the Wilcoxon Signed Rank Test 43
3.3.3 Sample Wilcoxon Signed Rank Test (Large Data Samples) 45
3.4 Computing the Sign Test 49
3.4.1 Sample Sign Test (Small Data Samples) 50
3.4.2 Sample Sign Test (Large Data Samples) 53
3.5 Performing the Wilcoxon Signed Rank Test and the Sign Test Using SPSS 57
3.5.1 Defi ne Your Variables 57
3.5.2 Type in Your Values 57
3.5.3 Analyze Your Data 58
3.5.4 Interpret the Results from the SPSS Output Window 58
3.6 Statistical Power 60
3.7 Examples from the Literature 61
3.8 Summary 61
3.9 Practice Questions 62
3.10 Solutions to Practice Questions 65
CHAPTER 4 COMPARING TWO UNRELATED SAMPLES: THE MANN.WHITNEY U-TEST AND THE KOLMOGOROV.SMIRNOV TWO-SAMPLE TEST 69
4.1 Objectives 69
4.2 Introduction 69
4.3 Computing the Mann.Whitney U-Test Statistic 70
4.3.1 Sample Mann.Whitney U-Test (Small Data Samples) 71
4.3.2 Confi dence Interval for the Difference between Two Location Parameters 74
4.3.3 Sample Mann.Whitney U-Test (Large Data Samples) 75
4.4 Computing the Kolmogorov-Smirnov Two-Sample Test Statistic 80
4.4.1 Sample Kolmogorov-Smirnov Two-Sample Test 81
4.5 Performing the Mann-Whitney U-Test and the Kolmogorov-Smirnov Two-Sample Test Using SPSS 84
4.5.1 Defi ne Your Variables 84
4.5.2 Type in Your Values 85
4.5.3 Analyze Your Data 86
4.5.4 Interpret the Results from the SPSS Output Window 86
4.6 Examples from the Literat
About the author
Greg W. Corder is Adjunct Instructor in the Department of Physics and Astronomy at James Madison University. He is also Adjunct Instructor of graduate education at Mary Baldwin College.
Dale I. Foreman is Professor Emeritus in the School of Education and Human Development at Shenandoah University.
Summary
"...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." -CHOICE
This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes:
* New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power
* SPSS(r) (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures
* Data sets and odd-numbered solutions provided in an appendix, and tables of critical values
* Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.
