scipy.stats.mstats.brunnermunzel#
- scipy.stats.mstats.brunnermunzel(x, y, alternative='two-sided', distribution='t')[source]#
Computes the Brunner-Munzel test on samples x and y
Missing values in x and/or y are discarded.
- Parameters
- x, yarray_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
- statisticfloat
The Brunner-Munzer W statistic.
- pvaluefloat
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
, seescipy.stats.brunnermunzel
.