Kruskal—Wallis
Kathleen F. Weaver, Vanessa Morales, Sarah L. Dunn, Kanya Godde, Pablo F. Weaver · 2017
A commonly used nonparametric test is the two- or more sample Kruskal-Wallis test. The Kruskal-Wallis is considered the nonparametric analogue to the parametric, one-way ANOVA. The Kruskal-Wallis is most applicable when comparing two or more samples; the data within each of the multiple samples do not need to follow a normal distribution. As with one-way ANOVA, the test aims to determine if there is an overall difference among the various sampling groups; also similar to one-way ANOVA, the Kruskal-Wallis lacks the ability to specify where the difference lies between groups. The Kruskal-Wallis test is most applicable when certain conditions and assumptions are fulfilled. In the chapter, statistical programs are used to perform a Kruskal-Wallis and determine the significance (p-value) for statistical analysis. And also, the medians or mean ranks of three or more groups or samples are evaluated and a logical conclusion for each dataset is constructed.