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  2. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/KruskalWallis_test

    kruskal.test (Ozone ~ Month, data = airquality) Kruskal-Wallis rank sum test data: Ozone by Month Kruskal-Wallis chi-squared = 29.267, df = 4, p-value = 6.901e-06 To determine which months differ, post-hoc tests may be performed using a Wilcoxon test for each pair of months, with a Bonferroni (or other) correction for multiple hypothesis testing.

  3. Median test - Wikipedia

    en.wikipedia.org/wiki/Median_test

    The test has low power (efficiency) for moderate to large sample sizes. The Wilcoxon–Mann–Whitney U two-sample test or its generalisation for more samples, the KruskalWallis test, can often be considered instead. The relevant aspect of the median test is that it only considers the position of each observation relative to the overall ...

  4. Wilcoxon signed-rank test - Wikipedia

    en.wikipedia.org/wiki/Wilcoxon_signed-rank_test

    The one-sample Wilcoxon signed-rank test can be used to test whether data comes from a symmetric population with a specified center (which corresponds to median, mean and pseudomedian). [11] If the population center is known, then it can be used to test whether data is symmetric about its center.

  5. Van der Waerden test - Wikipedia

    en.wikipedia.org/wiki/Van_der_Waerden_test

    The most common non-parametric test for the one-factor model is the Kruskal-Wallis test. The Kruskal-Wallis test is based on the ranks of the data. The advantage of the Van Der Waerden test is that it provides the high efficiency of the standard ANOVA analysis when the normality assumptions are in fact satisfied, but it also provides the ...

  6. Rank test - Wikipedia

    en.wikipedia.org/wiki/Rank_test

    In statistics, a rank test is any test involving ranks. ... Wilcoxon signed-rank test; KruskalWallis one-way analysis of variance. Mann–Whitney U (special case)

  7. Mann–Whitney U test - Wikipedia

    en.wikipedia.org/wiki/Mann–Whitney_U_test

    The Mann–Whitney test (also called the Mann–Whitney–Wilcoxon (MWW/MWU), Wilcoxon rank-sum test, or Wilcoxon–Mann–Whitney test) is a nonparametric statistical test of the null hypothesis that, for randomly selected values X and Y from two populations, the probability of X being greater than Y is equal to the probability of Y being greater than X.

  8. Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_statistics

    KruskalWallis one-way analysis of variance by ranks: tests whether > 2 independent samples are drawn from the same distribution. Kuiper's test: tests whether a sample is drawn from a given distribution, sensitive to cyclic variations such as day of the week. Logrank test: compares survival distributions of two right-skewed, censored samples.

  9. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Exactness: A test can be exact or be asymptotic delivering approximate results. ... Kruskal-Wallis test [11] Wilcoxon signed-rank test: interval: non-parametric ...