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  2. Mann–Whitney U test - Wikipedia

    en.wikipedia.org/wiki/Mann–Whitney_U_test

    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.

  3. 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). [12] If the population center is known, then it can be used to test whether data is symmetric about its center.

  4. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/Kruskal–Wallis_test

    The Kruskal–Wallis test' by ranks, Kruskal–Wallis test (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks is a non-parametric statistical test for testing whether samples originate from the same distribution. [ 1 ][ 2 ][ 3 ] It is used for comparing two or more independent samples of equal or different sample sizes.

  5. Sign test - Wikipedia

    en.wikipedia.org/wiki/Sign_test

    The sign test is a statistical test for consistent differences between pairs of observations, such as the weight of subjects before and after treatment. Given pairs of observations (such as weight pre- and post-treatment) for each subject, the sign test determines if one member of the pair (such as pre-treatment) tends to be greater than (or less than) the other member of the pair (such as ...

  6. Brunner Munzel Test - Wikipedia

    en.wikipedia.org/wiki/Brunner_Munzel_Test

    In statistics, the Brunner Munzel test[1][2][3] (also called the generalized Wilcoxon test) is a nonparametric 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. It is thus highly similar to the well-known ...

  7. Rank correlation - Wikipedia

    en.wikipedia.org/wiki/Rank_correlation

    Dave Kerby (2014) recommended the rank-biserial as the measure to introduce students to rank correlation, because the general logic can be explained at an introductory level. The rank-biserial is the correlation used with the Mann–Whitney U test, a method commonly covered in introductory college courses on statistics. The data for this test ...

  8. Rank test - Wikipedia

    en.wikipedia.org/wiki/Rank_test

    Download as PDF; Printable version; ... In statistics, a rank test is any test involving ranks. ... Wilcoxon signed-rank test;

  9. Siegel–Tukey test - Wikipedia

    en.wikipedia.org/wiki/Siegel–Tukey_test

    To test the difference between groups for significance a Wilcoxon rank sum test is used, which also justifies the notation W A and W B in calculating the rank sums. From the rank sums the U statistics are calculated by subtracting off the minimum possible score, n(n + 1)/2 for each group: [1] U A = 54 − 7(8)/2 = 26 U B = 37 − 6(7)/2 = 16