Non-Parametric Tests
Non-parametric tests are statistical tests that do not require the data to be normally distributed or have equal variances. These tests are used when the assumptions of parametric tests are not met or when the data is ordinal or nominal. Non-parametric tests are also known as distribution-free tests because they do not make any assumptions about the underlying distribution of the data. Examples of non-parametric tests include the Wilcoxon rank-sum test, Kruskal-Wallis test, and Mann-Whitney U test.
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