def METHOD_NAME(self):
    """Test function bayesfactor_ttest."""
    # check for approximate equality with 1e-3 tolerance
    # (as this is how we store the values here)
    assert bayesfactor_ttest(3.5, 20, 20) == appr(26.743)
    assert bayesfactor_ttest(3.5, 20) == appr(17.185)
    assert bayesfactor_ttest(3.5, 20, 1) == appr(17.185)
    # Compare against BayesFactor::testBF
    # >>> ttestBF(df$x, df$y, paired = FALSE, rscale = "medium")
    assert ttest(x, y).at["T-test", "BF10"] == "0.183"
    assert ttest(x, y, paired=True).at["T-test", "BF10"] == "0.135"
    assert int(float(ttest(x, z).at["T-test", "BF10"])) == 1290
    assert int(float(ttest(x, z, paired=True).at["T-test", "BF10"])) == 420
    # Now check the alternative tails
    assert bayesfactor_ttest(3.5, 20, 20, alternative="greater") > 1
    assert bayesfactor_ttest(3.5, 20, 20, alternative="less") < 1
    assert bayesfactor_ttest(-3.5, 20, 20, alternative="greater") < 1
    assert bayesfactor_ttest(-3.5, 20, 20, alternative="less") > 1
    # Check with wrong T-value
    assert np.isnan(bayesfactor_ttest(np.nan, 20, paired=True))