Nonparametric tests do not necessarily test differences between means .

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Nonparametric tests are used when assumptions for parametric tests, such as normal distribution and equal variances, are not met. They test for differences between groups or variables but not necessarily for differences in means. Nonparametric tests are based on ranks, medians, and other distributional attributes of the data, rather than on the actual values. Examples of nonparametric tests include the Mann-Whitney U test, Wilcoxon signed-rank test, Kruskal-Wallis test, and Friedman test.

Nonparametric Tests Do Not Necessarily Test Differences Between Means