scipy.stats.mannwhitneyu

scipy.stats.mannwhitneyu(x, y, use_continuity=True)

Computes the Mann-Whitney rank test on samples x and y.

Parameters:

• y (x,) -- Array of samples, should be one-dimensional.
• use_continuity (bool, optional) -- Whether a continuity correction (1/2.) should be taken into account. Default is True.

Returns:

• u (float) -- The Mann-Whitney statistics.
• prob (float) -- One-sided p-value assuming a asymptotic normal distribution.

Notes

Use only when the number of observation in each sample is > 20 and you have 2 independent samples of ranks. Mann-Whitney U is significant if the u-obtained is LESS THAN or equal to the critical value of U.

This test corrects for ties and by default uses a continuity correction. The reported p-value is for a one-sided hypothesis, to get the two-sided p-value multiply the returned p-value by 2.