Nonparametric Statistics

This "Second Edition" presents nonparametric statistical procedures in a clear manner and was specifically written for readers with a background in the social, behavioral, and health sciences. The book continues to follow the same format in all chapters to aid in reader comprehension, and each chapter begins with a general introduction and a list of the chapter's main learning objectives. A nonparametric procedure is then presented and is followed by context-based examples in a step-by-step fashion. Next, updated SPSS(R) screen captures are used to demonstrate how to perform and how to identify the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Additional tests including the sign test and the Kolmogorov-Smirnov two sample test have been added in addition to new coverage on statistical power. Data sets and odd-numbered solutions are provided in an appendix, and tables of critical values are also provided for reader reference. The authors have also prepared new 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. Chapter coverage includes: Nonparametric Statistics: An Introduction; Testing Your Data for Normality; Comparing Two Related Samples: The Wilcoxon Signed Rank Test; Comparing Two Unrelated Samples: The Mann-Whitney U Test; Comparing More Than Two Related Samples: Friedman's Test; Comparing More Than Two Unrelated Samples: Kruskal-Wallis H Test; Comparing Variables of Ordinal or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, and Biserial Correlations; Tests for Nominal Scale Data: Chi-Square Tests; and Test for Randomness: Runs Test.