The Mann-Whitney test - a non-parametric method

Instead of transforming the data to normality, we could employ one of a range of procedures referred to as non-parametric tests . These partially duplicate the functionality of tests we have already met, but use a method of calculation that does not depend upon a normal distribution. The non-parametric test that is generally substituted for the two sample f-test goes by a variety of names, but is most commonly called the Mann-Whitney test. 

In non-parametric tests the data are transformed into rank values and then all further calculations are based solely upon these rankings. 

All further calculations are then carried out on these rank values rather than on the original data. The next stage is to add up all the rank values for the two groups to 

When a /-test produces a significant outcome, its interpretation is quite straightforward- there is evidence that the two population mean values differ. Unfortunately, with non-parametric tests such as Mann-Whitney, it is not so simple. The conclusion 

Strictly speaking, because no mean or median is even calculated as part of the test, the null hypothesis should be that  

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