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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.
[2] [3] [4] It has an integrated spreadsheet for data input and can import files in several formats (Excel, SPSS, CSV, ...). 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 ...
Analyse-it provides a range of standard parametric and non-parametric procedures, including Descriptive statistics, ANOVA, ANCOVA, Mann–Whitney, Wilcoxon, chi-square, correlation, linear regression, logistic regression, polynomial regression and advanced model fitting, principal component analysis, and factor analysis.
The Wilcoxon–Mann–Whitney U two-sample test or its generalisation for more samples, the Kruskal–Wallis 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 median, whereas the Wilcoxon–Mann–Whitney test takes the ranks of each ...
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 ...
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.
Mann–Whitney U test; Wilcoxon signed-rank test; Van der Waerden test; The distribution of values in decreasing order of rank is often of interest when values vary widely in scale; this is the rank-size distribution (or rank-frequency distribution), for example for city sizes or word frequencies. These often follow a power law.
The core difference is that the Mann-Whitney U test assumes equal variances and a location shift model, while the Brunner Munzel test does not require these assumptions, making it more robust and applicable to a wider range of conditions. As a result, multiple authors recommend using the Brunner Munzel instead of the Mann-Whitney U test by default.
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