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NON-PARAMETRIC STATISTICS
Nonparametric tests are the opposite of parametric tests and are very useful when the parametric test assumptions are violated or the sample size is small. Most nonparametric tests examine the distribution of data rather than the raw data itself.

List of non-parametric test


 * Mann-Whitney test
 * Wilcoxon rank-sum test
 * Kruskal-Wallis test
 * Chi-Square test

Mann-Whitney test/Wilcoxon rank-sum test

When the distributional assumption of the independent sample t-test is violated, the nonparametric counterparts, the Wilcoxon rank-sum test and the Mann-Whitney test, are used to make group comparisons.



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Kruskal-Wallis test
When comparing three or more independent groups, the Kruskal-Wallis test can be used instead of the one-way ANOVA.



Chi-Square test
The Chi-Square test is the most straightforward method for analyzing categorical variables. Because the data is nominal or ordinal, it is a nonparametric test.

