Assumptions #1, #2 and #3 are explained below: If these assumptions are not met, there is likely to be a different statistical test that you can use instead. However, you should check whether your study meets these three assumptions before moving on. You cannot test the first three of these assumptions with Minitab because they relate to your study design and choice of variables. The Mann-Whitney U test has four "assumptions". However, before we introduce you to this procedure, you need to understand the different assumptions that your data must meet in order for a Mann-Whitney U test to give you a valid result.
#T test minitab how to#
In this guide, we show you how to carry out a Mann-Whitney U test using Minitab, as well as interpret and report the results from this test. Alternately, you could use a Mann-Whitney U test to determine whether there is a difference in typing speed based on room lighting (i.e., the dependent variable would be "typing speed" and the independent variable would be "room lighting", which has two groups: "red lighting" and "blue lighting"). The Mann-Whitney U test determines whether there is a statistically significant difference between two unrelated, independent groups on a dependent variable.įor example, you could use a Mann-Whitney U test to determine whether there is a difference in test anxiety between undergraduate and postgraduate students (i.e., the dependent variable would be "test anxiety", and the independent variable would be "educational level", which has two groups: "undergraduate students" and "postgraduate students"). Mann-Whitney U test using Minitab Introduction
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