scipy.stats.mstats.brunnermunzel

scipy.stats.mstats.brunnermunzel(x, y, alternative='two-sided', distribution='t')

Computes the Brunner-Munzel test on samples x and y

Missing values in x and/or y are discarded.

Parameters:

x, y : array_like

Array of samples, should be one-dimensional.

alternative : ‘less’, ‘two-sided’, or ‘greater’, optional

Whether to get the p-value for the one-sided hypothesis (‘less’ or ‘greater’) or for the two-sided hypothesis (‘two-sided’). Defaults value is ‘two-sided’ .

distribution: ‘t’ or ‘normal’, optional

Whether to get the p-value by t-distribution or by standard normal distribution. Defaults value is ‘t’ .

Returns:

statistic : float

The Brunner-Munzer W statistic.

pvalue : float

p-value assuming an t distribution. One-sided or two-sided, depending on the choice of alternative and distribution.

See also

mannwhitneyu

Mann-Whitney rank test on two samples.

Notes

For more details on brunnermunzel, see stats.brunnermunzel.