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  2. 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.

  3. MedCalc - Wikipedia

    en.wikipedia.org/wiki/MedCalc

    MedCalc includes basic parametric and non-parametric statistical procedures and graphs such as descriptive statistics, ANOVA, Mann–Whitney test, Wilcoxon test, χ 2 test, correlation, linear as well as non-linear regression, logistic regression, and multivariate statistics. [5]

  4. 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.

  5. Hodges–Lehmann estimator - Wikipedia

    en.wikipedia.org/wiki/Hodges–Lehmann_estimator

    In statistics, the Hodges–Lehmann estimator is a robust and nonparametric estimator of a population's location parameter.For populations that are symmetric about one median, such as the Gaussian or normal distribution or the Student t-distribution, the Hodges–Lehmann estimator is a consistent and median-unbiased estimate of the population median.

  6. Rank correlation - Wikipedia

    en.wikipedia.org/wiki/Rank_correlation

    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 consists of two groups; and for each member of the groups, the outcome is ranked for the study as a whole.

  7. 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.

  8. Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_statistics

    Mann–Whitney U or Wilcoxon rank sum test: tests whether two samples are drawn from the same distribution, as compared to a given alternative hypothesis. McNemar's test: tests whether, in 2 × 2 contingency tables with a dichotomous trait and matched pairs of subjects, row and column marginal frequencies are equal.

  9. Friedman test - Wikipedia

    en.wikipedia.org/wiki/Friedman_test

    The Wilcoxon signed-rank test is a nonparametric test of nonindependent data from only two groups. The Skillings–Mack test is a general Friedman-type statistic that can be used in almost any block design with an arbitrary missing-data structure. The Wittkowski test is a general Friedman-Type statistics similar to Skillings-Mack test. When the ...