Title:
Nonparametric statistics : a step-by-step approach
Personal Author:
Edition:
2nd ed.
Publication Information:
Hoboken : Wiley, 2014.
Physical Description:
xiv, 267p. : ill. ; 25 cm.
ISBN:
9781118840313
Added Author:
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 33000000008572 | QA278.8 C67 2014 | Open Access Book | Book | Searching... |
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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
Preface | p. ix |
List of Variables | p. xiii |
Chapter 1 Nonparametric Statistics: An Introduction | p. 1 |
1.1 Objectives | p. 1 |
1.2 Introduction | p. 1 |
1.3 The Nonparametric Statistical Procedures Presented in This Book | p. 3 |
1.3.1 State the Null and Research Hypotheses | p. 4 |
1.3.2 Set the Level of Risk (or the Level of Significance) Associated with the Null Hypothesis | p. 4 |
1.3.3 Choose the Appropriate Test Statistic | p. 5 |
1.3.4 Compute the Test Statistic | p. 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 | p. 5 |
1.3.6 Compare the Obtained Value with the Critical Value | p. 6 |
1.3.7 Interpret the Results | p. 6 |
1.3.8 Reporting the Results | p. 6 |
1.4 Ranking Data | p. 6 |
1.5 Ranking Data with Tied Values | p. 7 |
1.6 Counts of Observations | p. 8 |
1.7 Summary | p. 9 |
1.8 Practice Questions | p. 9 |
1.9 Solutions to Practice Questions | p. 10 |
Chapter 2 Testing Data for Normality | |
2.1 Objectives | p. 13 |
2.2 Introduction | p. 13 |
2.3 Describing Data and the Normal Distribution | p. 14 |
2.4 Computing and Testing Kurtosis and Skewness for Sample Normality | p. 17 |
2.4.1 Sample Problem for Examining Kurtosis | p. 19 |
2.4.2 Sample Problem for Examining Skewness | p. 22 |
2.4.3 Examining Skewness and Kurtosis for Normality Using SPSS | p. 24 |
2.5 Computing the Kolmogorov-Smirnov One-Sample Test | p. 27 |
2.5.1 Sample Kofmogorov-Smirnov One-Sample Test | p. 29 |
2.5.2 Performing the Kolmogorov-Smirnov One-Sample Test Using SPSS | p. 34 |
2.6 Summary | p. 37 |
2.7 Practice Questions | p. 37 |
2.8 Solutions to Practice Questions | p. 38 |
Chapter 3 Comparing Two Related Samples: The Wilcoxon Signed Rank and the Sign Test | p. 39 |
3.1 Objectives | p. 39 |
3.2 Introduction | p. 39 |
3.3 Computing the Wilcoxon Signed Rank Test Statistic | p. 40 |
3.3.1 Sample Wilcoxon Signed Rank Test (Small Data Samples) | p. 41 |
3.3.2 Confidence Interval for the Wilcoxon Signed Rank Test | p. 43 |
3.3.3 Sample Wilcoxon Signed Rank Test (Large Data Samples) | p. 45 |
3.4 Computing the Sign Test | p. 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 SPSS | p. 57 |
3.5.1 Define Your Variables | p. 57 |
3.5.2 Type in Your Values | p. 57 |
3.5.3 Analyze Your Data | p. 58 |
3.5.4 Interpret the Results from the SPSS Output Window | p. 58 |
3.6 Statistical Power | p. 60 |
3.7 Examples from the Literature | p. 61 |
3.8 Summary | p. 61 |
3.9 Practice Questions | p. 62 |
3.10 Solutions to Practice Questions | p. 65 |
Chapter 4 Comparing Two Unrelated Samples: The Mann-Whitney U-Test and the Kolmogorov-Smirnov Two-Sample Test | p. 69 |
4.1 Objectives | p. 69 |
4.2 Introduction | p. 69 |
4.3 Computing the Mann-Whitney U-Test Statistic | p. 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 Parameters | p. 74 |
4.3.3 Sample Mann-Whitney U-Test (Large Data Samples) | p. 75 |
4.4 Computing the Kolmogorov-Smirnov Two-Sample Test Statistic | p. 80 |
4.4.1 Sample Kolmogorov-Smirnov Two-Sample Test | p. 81 |
4.5 Performing the Mann-Whitney C-Test and the Kolmogorov-Smirnov Two-Sample Test Using SPSS | p. 84 |
4.5.1 Define Your Variables | p. 84 |
4.5.2 Type in Your Values | p. 85 |
4.5.3 Analyze Your Data | p. 86 |
4.5.4 Interpret the Results from the SPSS Output Window | p. 86 |
4.6 Examples from the Literature | p. 88 |
4.7 Summary | p. 89 |
4.8 Practice Questions | p. 90 |
4.9 Solutions to Practice Questions | p. 92 |
Chapter 5 Comparing More Than Two Related Samples: The Friedman Test | |
5.1 Objectives | p. 97 |
5.2 Introduction | p. 97 |
5.3 Computing the Friedman Test Statistic | p. 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 SPSS | p. 105 |
5.3.4 Sample Friedman's Test (Large Data Samples without Ties) | p. 108 |
5.4 Examples from the Literature | p. 111 |
5.5 Summary | p. 112 |
5.6 Practice Questions | p. 113 |
5.7 Solutions to Practice Questions | p. 114 |
Chapter 6 Comparing More Than Two Unrelated Samples: The Kruskal-Wallis H-Test | p. 117 |
6.1 Objectives | p. 117 |
6.2 Introduction | p. 117 |
6.3 Computing the Kruskal-Wallis F-Test Statistic | p. 118 |
6.3.1 Sample Kruskal-Wallis ff-Test (Small Data Samples) | p. 119 |
6.3.2 Performing the Kruskal-Wallis H-Test Using SPSS | p. 124 |
6.3.3 Sample Kruskal-Wallis ff-Test (Large Data Samples) | p. 128 |
6.4 Examples from the Literature | p. 134 |
6.5 Summary | p. 134 |
6.6 Practice Questions | p. 135 |
6.7 Solutions to Practice Questions | p. 136 |
Chapter 7 Comparing Variables of Ordinal or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, and Biserial Correlations | p. 139 |
7.1 Objectives | p. 139 |
7.2 Introduction | p. 139 |
7.3 The Correlation Coefficient | p. 140 |
7.4 Computing the Spearman Rank-Order Correlation Coefficient | p. 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 SPSS | p. 148 |
7.5 Computing the Point-Biserial and Biserial Correlation Coefficients | p. 150 |
7.5.1 Correlation of a Dichotomous Variable and an Interval Scale Variable | p. 150 |
7.5.2 Correlation of a Dichotomous Variable and a Rank-Order Variable | p. 152 |
7.5.3 Sample Point-Biserial Correlation (Small Data Samples) | p. 152 |
7.5.4 Performing the Point-Biserial Correlation Using SPSS | p. 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 SPSS | p. 167 |
7.6 Examples from the Literature | p. 167 |
7.7 Summary | p. 167 |
7.8 Practice Questions | p. 168 |
7.9 Solutions to Practice Questions | p. 170 |
Chapter 8 Tests for Nominal Scale Data: Chi-Square and Fisher Exact Tests | p. 172 |
8.1 Objectives | p. 172 |
8.2 Introduction | p. 172 |
8.3 The ¿ 2 Goodness-of-Fit Test | p. 172 |
8.3.1 Computing the ¿ 2 Goodness-of-Fit Test Statistic | p. 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 SPSS | p. 180 |
8.4 The ¿ 2 Test for Independence | p. 184 |
8.4.1 Computing the ¿ 2 Test for Independence | p. 185 |
8.4.2 Sample ¿ 2 Test for Independence | p. 186 |
8.4.3 Performing the ¿ 2 Test for Independence Using SPSS | p. 190 |
8.5 The Fisher Exact Test | p. 196 |
8.5.1 Computing the Fisher Exact Test for 2 × 2 Tables | p. 197 |
8.5.2 Sample Fisher Exact Test | p. 197 |
8.5.3 Performing the Fisher Exact Test Using SPSS | p. 201 |
8.6 Examples from the Literature | p. 202 |
8.7 Summary | p. 203 |
8.8 Practice Questions | p. 204 |
8.9 Solutions to Practice Questions | p. 206 |
Chapter 9 Test for Randomness: The Runs Test | p. 210 |
9.1 Objectives | p. 210 |
9.2 Introduction | p. 210 |
9.3 The Runs Test for Randomness | p. 210 |
9.3.1 Sample Runs Test (Small Data Samples) | p. 212 |
9.3.2 Performing the Runs Test Using SPSS | p. 213 |
9.3.3 Sample Runs Test (Large Data Samples) | p. 217 |
9.3.4 Sample Runs Test Referencing a Custom Value | p. 219 |
9.3.5 Performing the Runs Test for a Custom Value Using SPSS | p. 221 |
9.4 Examples from the Literature | p. 225 |
9.5 Summary | p. 225 |
9.6 Practice Questions | p. 225 |
9.7 Solutions to Practice Questions | p. 227 |
Appendix A SPSS At a Glance | p. 229 |
Appendix B Critical Value Tables | p. 235 |
References | p. 261 |
Index | p. 265 |