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# scipy.stats.mstats.pointbiserialr

`scipy.stats.mstats.``pointbiserialr`(x, y)

  Calculates a point biserial correlation coefficient and the associated p-value.

  > The point biserial correlation is used to measure the relationship between a binary variable, x, and a continuous variable, y. Like other correlation coefficients, this one varies between -1 and +1 with 0 implying no correlation. Correlations of -1 or +1 imply a determinative relationship.

  > This function uses a shortcut formula but produces the same result as `pearsonr`.

  Parameters : | x : array_like of bools Input array. y : array_like Input array.
  Returns : | r : float R value p-value : float 2-tailed p-value

  Notes

  Missing values are considered pair-wise: if a value is missing in x, the corresponding value in y is masked.

  Examples

      >>> from scipy import stats
      >>> a = np.array([0, 0, 0, 1, 1, 1, 1])
      >>> b = np.arange(7)
      >>> stats.pointbiserialr(a, b)
      (0.8660254037844386, 0.011724811003954652)
      >>> stats.pearsonr(a, b)
      (0.86602540378443871, 0.011724811003954626)
      >>> np.corrcoef(a, b)
      array([[ 1.       ,  0.8660254],
             [ 0.8660254,  1.       ]])

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