ABSTRACT
This chapter covers the broad field of nonparametric statistics and presents in-depth information about four of those that are commonly used: Mann-Whitney U test, Wilcoxon signed-rank test, Kruskal-Wallis test, and the chi-square test of independence. After explaining why nonparametric tests are necessary (i.e., when assumptions of parametric tests, such as normally distributed data, are violated), each of these four statistics are described in depth. These detailed descriptions each include discussions of when the statistic is appropriate to use, the analogous parametric statistic for each nonparametric counterpart, an example that illustrates how to calculate and interpret each statistic, and considerations of other situations that may require variations on the methods used for each statistic. The chapter includes information about how to read and interpret tables of critical values for each of these statistics and walks the reader through how to interpret output from the chi-square analysis conducted on Statistical Package for the Social Sciences (SPSS).
