AUC = U n1n2 A U C = U n 1 n 2. It looks convincing, but I made some checks on real data in R and I found that, indeed, there is a functional relationship between U U and AUC A U C, but it has slightly different form: AUC = 1 − U n1n2 A U C = 1 − U n 1 n 2. Unfortunately I cannot share the real data I used, but here is a simple simulation 1 Answer. Sorted by: 1. You cannot directly compare a t-test with the Mann Whitney U test. You can use the Mann Whitney test as an alternative to a t-test when the assumptions of a t-test cannot be met. The Mann Whitney U test is a nonparametric test that requires weaker assumptions, so it is often used in place of the t-test. The unpaired two-samples Wilcoxon test (also known as Wilcoxon rank sum test or Mann-Whitney test) is a non-parametric alternative to the unpaired two-samples t-test, which can be used to compare two independent groups of samples. It's used when your data are not normally distributed. Related Book: The most widely used nonparametric rank test is the Mann-Whitney-Wilcoxon rank sum test (abbreviated MWW) (This test is also commonly called Wilcoxon-Mann-Whitney test and abbreviated as WMW.) (see Wilcoxon-Mann-Whitney Test). The Wilcoxon Rank Sum Test, sometimes called the Mann Whitney Wilcoxon Test or Mann Whitney U test, is used to test whether two independent samples come from the same population or two different populations.. Since the Wilcoxon Rank Sum Test is a form of hypothesis testing, there will be an associated null and alternative hypothesis.The test is used for continuous data. A popular nonparametric test to compare outcomes between two independent groups is the Mann Whitney U test. The Mann Whitney U test, sometimes called the Mann Whitney Wilcoxon Test or the Wilcoxon Rank Sum Test, is used to test whether two samples are likely to derive from the same population (i.e., that the two populations have the same shape). FGSXb5.

what is wilcoxon mann whitney test