Cover image for Nonparametric statistics : a step-by-step approach
Title:
Nonparametric statistics : a step-by-step approach
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Edition:
2nd ed.
Publication Information:
Hoboken : Wiley, 2014.
Physical Description:
xiv, 267p. : ill. ; 25 cm.
ISBN:
9781118840313
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33000000008572 QA278.8 C67 2014 Open Access Book Book
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Summary

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® (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.


Author Notes

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.


Table of Contents

Prefacep. ix
List of Variablesp. xiii
Chapter 1 Nonparametric Statistics: An Introductionp. 1
1.1 Objectivesp. 1
1.2 Introductionp. 1
1.3 The Nonparametric Statistical Procedures Presented in This Bookp. 3
1.3.1 State the Null and Research Hypothesesp. 4
1.3.2 Set the Level of Risk (or the Level of Significance) Associated with the Null Hypothesisp. 4
1.3.3 Choose the Appropriate Test Statisticp. 5
1.3.4 Compute the Test Statisticp. 5
1.3.5 Determine the Value Needed for Rejection of the Null Hypothesis Using the Appropriate Table of Critical Values for the Particular Statisticp. 5
1.3.6 Compare the Obtained Value with the Critical Valuep. 6
1.3.7 Interpret the Resultsp. 6
1.3.8 Reporting the Resultsp. 6
1.4 Ranking Datap. 6
1.5 Ranking Data with Tied Valuesp. 7
1.6 Counts of Observationsp. 8
1.7 Summaryp. 9
1.8 Practice Questionsp. 9
1.9 Solutions to Practice Questionsp. 10
Chapter 2 Testing Data for Normality
2.1 Objectivesp. 13
2.2 Introductionp. 13
2.3 Describing Data and the Normal Distributionp. 14
2.4 Computing and Testing Kurtosis and Skewness for Sample Normalityp. 17
2.4.1 Sample Problem for Examining Kurtosisp. 19
2.4.2 Sample Problem for Examining Skewnessp. 22
2.4.3 Examining Skewness and Kurtosis for Normality Using SPSSp. 24
2.5 Computing the Kolmogorov-Smirnov One-Sample Testp. 27
2.5.1 Sample Kofmogorov-Smirnov One-Sample Testp. 29
2.5.2 Performing the Kolmogorov-Smirnov One-Sample Test Using SPSSp. 34
2.6 Summaryp. 37
2.7 Practice Questionsp. 37
2.8 Solutions to Practice Questionsp. 38
Chapter 3 Comparing Two Related Samples: The Wilcoxon Signed Rank and the Sign Testp. 39
3.1 Objectivesp. 39
3.2 Introductionp. 39
3.3 Computing the Wilcoxon Signed Rank Test Statisticp. 40
3.3.1 Sample Wilcoxon Signed Rank Test (Small Data Samples)p. 41
3.3.2 Confidence Interval for the Wilcoxon Signed Rank Testp. 43
3.3.3 Sample Wilcoxon Signed Rank Test (Large Data Samples)p. 45
3.4 Computing the Sign Testp. 49
3.4.1 Sample Sign Test (Small Data Samples)p. 50
3.4.2 Sample Sign Test (Large Data Samples)p. 53
3.5 Performing the Wilcoxon Signed Rank Test and the Sign Test Using SPSSp. 57
3.5.1 Define Your Variablesp. 57
3.5.2 Type in Your Valuesp. 57
3.5.3 Analyze Your Datap. 58
3.5.4 Interpret the Results from the SPSS Output Windowp. 58
3.6 Statistical Powerp. 60
3.7 Examples from the Literaturep. 61
3.8 Summaryp. 61
3.9 Practice Questionsp. 62
3.10 Solutions to Practice Questionsp. 65
Chapter 4 Comparing Two Unrelated Samples: The Mann-Whitney U-Test and the Kolmogorov-Smirnov Two-Sample Testp. 69
4.1 Objectivesp. 69
4.2 Introductionp. 69
4.3 Computing the Mann-Whitney U-Test Statisticp. 70
4.3.1 Sample Mann-Whitney U-Test (Small Data Samples)p. 71
4.3.2 Confidence Interval for the Difference between Two Location Parametersp. 74
4.3.3 Sample Mann-Whitney U-Test (Large Data Samples)p. 75
4.4 Computing the Kolmogorov-Smirnov Two-Sample Test Statisticp. 80
4.4.1 Sample Kolmogorov-Smirnov Two-Sample Testp. 81
4.5 Performing the Mann-Whitney C-Test and the Kolmogorov-Smirnov Two-Sample Test Using SPSSp. 84
4.5.1 Define Your Variablesp. 84
4.5.2 Type in Your Valuesp. 85
4.5.3 Analyze Your Datap. 86
4.5.4 Interpret the Results from the SPSS Output Windowp. 86
4.6 Examples from the Literaturep. 88
4.7 Summaryp. 89
4.8 Practice Questionsp. 90
4.9 Solutions to Practice Questionsp. 92
Chapter 5 Comparing More Than Two Related Samples: The Friedman Test
5.1 Objectivesp. 97
5.2 Introductionp. 97
5.3 Computing the Friedman Test Statisticp. 98
5.3.1 Sample Friedman's Test (Small Data Samples without Ties)p. 99
5.3.2 Sample Friedman's Test (Small Data Samples with Ties)p. 101
5.3.3 Performing the Friedman Test Using SPSSp. 105
5.3.4 Sample Friedman's Test (Large Data Samples without Ties)p. 108
5.4 Examples from the Literaturep. 111
5.5 Summaryp. 112
5.6 Practice Questionsp. 113
5.7 Solutions to Practice Questionsp. 114
Chapter 6 Comparing More Than Two Unrelated Samples: The Kruskal-Wallis H-Testp. 117
6.1 Objectivesp. 117
6.2 Introductionp. 117
6.3 Computing the Kruskal-Wallis F-Test Statisticp. 118
6.3.1 Sample Kruskal-Wallis ff-Test (Small Data Samples)p. 119
6.3.2 Performing the Kruskal-Wallis H-Test Using SPSSp. 124
6.3.3 Sample Kruskal-Wallis ff-Test (Large Data Samples)p. 128
6.4 Examples from the Literaturep. 134
6.5 Summaryp. 134
6.6 Practice Questionsp. 135
6.7 Solutions to Practice Questionsp. 136
Chapter 7 Comparing Variables of Ordinal or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, and Biserial Correlationsp. 139
7.1 Objectivesp. 139
7.2 Introductionp. 139
7.3 The Correlation Coefficientp. 140
7.4 Computing the Spearman Rank-Order Correlation Coefficientp. 140
7.4.1 Sample Spearman Rank-Order Correlation (Small Data Samples without Ties)p. 142
7.4.2 Sample Spearman Rank-Order Correlation (Small Data Samples with Ties)p. 145
7.4.3 Performing the Spearman Rank-Order Correlation Using SPSSp. 148
7.5 Computing the Point-Biserial and Biserial Correlation Coefficientsp. 150
7.5.1 Correlation of a Dichotomous Variable and an Interval Scale Variablep. 150
7.5.2 Correlation of a Dichotomous Variable and a Rank-Order Variablep. 152
7.5.3 Sample Point-Biserial Correlation (Small Data Samples)p. 152
7.5.4 Performing the Point-Biserial Correlation Using SPSSp. 156
7.5.5 Sample Point-Biserial Correlation (Large Data Samples)p. 159
7.5.6 Sample Biserial Correlation (Small Data Samples)p. 163
7.5.7 Performing the Biserial Correlation Using SPSSp. 167
7.6 Examples from the Literaturep. 167
7.7 Summaryp. 167
7.8 Practice Questionsp. 168
7.9 Solutions to Practice Questionsp. 170
Chapter 8 Tests for Nominal Scale Data: Chi-Square and Fisher Exact Testsp. 172
8.1 Objectivesp. 172
8.2 Introductionp. 172
8.3 The ¿ 2 Goodness-of-Fit Testp. 172
8.3.1 Computing the ¿ 2 Goodness-of-Fit Test Statisticp. 173
8.3.2 Sample ¿ 2 Goodness-of-Fit Test (Category Frequencies Equal)p. 173
8.3.3 Sample ¿ 2 Goodness-of-Fit Test (Category Frequencies Not Equal)p. 176
8.3.4 Performing the ¿ 2 Goodness-of-Fit Test Using SPSSp. 180
8.4 The ¿ 2 Test for Independencep. 184
8.4.1 Computing the ¿ 2 Test for Independencep. 185
8.4.2 Sample ¿ 2 Test for Independencep. 186
8.4.3 Performing the ¿ 2 Test for Independence Using SPSSp. 190
8.5 The Fisher Exact Testp. 196
8.5.1 Computing the Fisher Exact Test for 2 × 2 Tablesp. 197
8.5.2 Sample Fisher Exact Testp. 197
8.5.3 Performing the Fisher Exact Test Using SPSSp. 201
8.6 Examples from the Literaturep. 202
8.7 Summaryp. 203
8.8 Practice Questionsp. 204
8.9 Solutions to Practice Questionsp. 206
Chapter 9 Test for Randomness: The Runs Testp. 210
9.1 Objectivesp. 210
9.2 Introductionp. 210
9.3 The Runs Test for Randomnessp. 210
9.3.1 Sample Runs Test (Small Data Samples)p. 212
9.3.2 Performing the Runs Test Using SPSSp. 213
9.3.3 Sample Runs Test (Large Data Samples)p. 217
9.3.4 Sample Runs Test Referencing a Custom Valuep. 219
9.3.5 Performing the Runs Test for a Custom Value Using SPSSp. 221
9.4 Examples from the Literaturep. 225
9.5 Summaryp. 225
9.6 Practice Questionsp. 225
9.7 Solutions to Practice Questionsp. 227
Appendix A SPSS At a Glancep. 229
Appendix B Critical Value Tablesp. 235
Referencesp. 261
Indexp. 265