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Wilcoxon-Test (Wilcoxon Signed Rank Test)

The Wilcoxon test, or Wilcoxon signed-rank test, checks whether two dependent samples differ significantly from each other. The Wilcoxon test is a non-parametric test and is therefore subject to significantly lower requirements than its parametric counterpart, the t-test for dependent samples. Thus, as soon as the boundary conditions for the t-test for dependent samples are no longer fulfilled, the Wilcoxon test is used. Assumptions Wilcoxon test Since the Wilcoxon test is a nonparametric test, the data need not be normally distributed. However, to calculate a Wilcoxon test, the samples must be dependent. Dependent samples are present, for example, when data are obtained from measurement repetition or when so-called natural pairs are involved. Measurement repetition: A characteristic of a person, e.g. weight, was measured at two points in time Natural pairs: The values do not come from the same person but from persons who belong together, for example lawyer/client, wife/husband and psychologist/patient. If the data are not available in pairs, the Mann-Whitney U test is used instead of the Wilcoxon test. Furthermore, the distribution shape of the differences of the two dependent samples should be approximately symmetrical. To the Wilcoxon Test Calculator https://datatab.net/statistics-calcul... More information about the Wilcoxon signed-rank test https://datatab.net/tutorial/wilcoxon...