# scipy.stats.contingency.expected_freq

scipy.stats.contingency.expected_freq(observed)

  Compute the expected frequencies from a contingency table.

  Given an n-dimensional contingency table of observed frequencies, compute the expected frequencies for the table based on the marginal sums under the assumption that the groups associated with each dimension are independent.

  Parameters
    observed array_like

      The table of observed frequencies. (While this function can handle a 1-D array, that case is trivial. Generally observed is at least 2-D.)

  Returns
    expected ndarray of float64

      The expected frequencies, based on the marginal sums of the table. Same shape as observed.

  Examples

      >>> from scipy.stats.contingency import expected_freq
      >>> observed = np.array([[10, 10, 20],[20, 20, 20]])
      >>> expected_freq(observed)
      array([[ 12.,  12.,  16.],
             [ 18.,  18.,  24.]])

scipy.stats.contingency.crosstab scipy.stats.contingency.margins