Kruskal‐Wallis Test
Patrick E. McKight, Julius Najab
Abstract
Patrick E. McKight, Julius Najab
Abstract
Abstract The Kruskal‐Wallis (Kruskal & Wallis, 1952) is a nonparametric statistical test that assesses the differences among three or more independently sampled groups on a single, non‐normally distributed continuous variable. Non‐normally distributed data (e.g., ordinal or rank data) are suitable for the Kruskal‐Wallis test. In contrast, the one‐way analysis of variance (ANOVA), which is a parametric test, may be used for a normally distributed continuous variable. The Kruskal‐Wallis test is an extension of the two‐group Mann‐Whitney U (Wilcoxon rank) test. Thus, the Kruskal‐Wallis is a more generalized form of the Mann‐Whitney U test and is the nonparametric version of the one‐way ANOVA.
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Abstract The Kruskal‐Wallis (Kruskal & Wallis, 1952) is a nonparametric statistical test that assesses the differences among three or more independently sampled groups on a single, non‐normally distributed continuous variable. Non‐normally distributed data (e.g., ordinal or rank data) are suitable for the Kruskal‐Wallis test. In contrast, the one‐way analysis of variance (ANOVA), which is a parametric test, may be used for a normally distributed continuous variable. The Kruskal‐Wallis test is an extension of the two‐group Mann‐Whitney U (Wilcoxon rank) test. Thus, the Kruskal‐Wallis is a more generalized form of the Mann‐Whitney U test and is the nonparametric version of the one‐way ANOVA.
Key concepts: Kruskal–Wallis one-way analysis of variance, Mann–Whitney U test, Nonparametric statistics, Kruskal's algorithm, Analysis of variance, Mathematics, Statistics, Wilcoxon signed-rank test