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 More information about the Wilcoxon signed-rank test
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