def _bonferroni(p_values, alpha):
    """
    Perform the `Bonferroni correction`_ on a set of p-values and test for significance.

    :param p_values: p-values to adjust for family-wise error rate
    :type p_values: sequence
    :param alpha: Confidence level between 0 and 1
    :type alpha: float
    :return: Whether or not each result was significant, and corrected p-values.
    :rtype: (numpy.array[bool], numpy.array[float])

    .. _`Bonferroni correction`: http://en.wikipedia.org/wiki/Bonferroni_correction
    """
    n = len(p_values)
    corrected_pvals = p_values*n

    return corrected_pvals < alpha, corrected_pvals