What is the difference between the Mann-Whitney and Wilcoxon rank-sumtest? [duplicate] Ask Question Asked 9 years, 3 months ago Modified 9 years, 3 months ago Viewed 65k times 16 This question already has answers here : Is the W statistic output by wilcox.test () in R the same as the U statistic? (3 answers) Closed 9 years ago. In reporting the results of a Mann-Whitney test, it is important to state: A measure of the central tendencies of the two groups (means or medians; since the Mann-Whitney is an ordinal test, medians are usually recommended) The value of U. The sample sizes. The significance level. 1. The Wilcoxon Mann Whitney test tests the null hypothesis that the distributions are the same. The alternative hypothesis is that the distributions are not the same. You've already examined the distributions and they don't "look" the same so there's good indication that the null will be rejected. This doesn't make the test invalid. This is a different test! In fact, it tests whether two groups have been drawn from the same population (regardless of what that population may be). In effect, this means it does much the same as the Mann-Whitney test! However, this test tends to have better power than the Mann-Whitney test when sample sizes are less than about 25 per group 💡 The Wilcoxon rank-sum test is sometimes called the Wilcoxon-Mann-Whitney test or a Mann-Whitney U-test, as it was proposed by Wilcoxon and further developed by Mann and Whitney.However, this development led to a slightly different version of the test, equivalent to the original one.The final decision is always the same, but the calculations are slightly different. It is possible that a more complex model would be a very good discriminator, however, and the Wilcoxon test does not comment on this. For instance, it could be that one group has values that tend to be very low or very high, while the other group has values that are in the middle. A Wilcoxon test of these two groups would show minimal differences. Highlights. T-tests assume data follow a normal distribution. Mann-Whitney tests are non-parametric and don't assume a specific data distribution. T-tests and Mann-Whitney tests are used to determine differences between two groups. The t-test assumes equal variances and independent observations. The Mann-Whitney test is a powerful tool for The Wilcoxon-Mann-Whitney test evaluates the difference in medians between two similarly shaped populations, which have the same variance. This nonparametric test is similar to the two-sample Student's t Test. b4Wto.