Mann-Whitney U Test

Mann-Whitney U test is the non-parametric alternative test to the independent sample t-test.  It is a non-parametric test that is used to compare two sample means that come from the same population, and used to test whether two sample means are equal or not.  Usually, the Mann-Whitney U test is used when the data is ordinal or when the assumptions of the t-test are not met.

Sometimes understanding the Mann-Whitney U is difficult interpret because the results are presented in group rank differences rather than group mean differences.  The Intellectus Statistics tool interprets the analysis in plain English!

Assumptions of the Mann-Whitney:

Mann-Whitney U test is a non-parametric test, so it does not assume any assumptions related to the distribution of scores.  There are, however, some assumptions that are assumed
1. The sample drawn from the population is random.
2. Independence within the samples and mutual independence is assumed.  That means that an observation is in one group or the other (it cannot be in both).
3. Ordinal measurement scale is assumed.

Where:
U=Mann-Whitney U test
N₁ = sample size one
N2= Sample size two
R_i = Rank of the sample size