# 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.

scipy.stats.mstats.friedmanchisquare scipy.stats.mstats.skewtest