def METHOD_NAME():
    class_labels = [0, 1, 2]
    y = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
    flagA = [1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1]
    flagB = [1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0]
    chi2_spd = statistical.class_bias(y, flagA, flagB, class_labels)
    answer = {
        0: (0.7093881150142265, -0.16666666666666663),
        1: (0.7093881150142265, 0.16666666666666669),
        2: (0.3613104285261789, 0.33333333333333337),
    }
    for key in class_labels:
        assert chi2_spd[key] == pytest.approx(answer[key])
    flagA = [1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0]
    chi2_spd = statistical.class_bias(y, flagA, flagB, class_labels)
    answer = {
        0: (0.025347318677468325, -1.0),
        1: (0.025347318677468325, -1.0),
        2: (0.17090352023079353, -0.5),
    }
    for key in class_labels:
        assert chi2_spd[key] == pytest.approx(answer[key])