def test_one_sample_test(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
ttest = tTest(y1=sal_a)
test_summary = ttest.test_summary
assert_almost_equal(test_summary['Sample 1 Mean'], np.mean(sal_a))
assert_almost_equal(test_summary['t-statistic'], 47.95382017797468)
assert_almost_equal(test_summary['p-value'], 2.220446049250313e-16)
assert test_summary['alternative'] == 'two-sided'
assert test_summary['test description'] == 'One-Sample t-test'
assert len(sal_a) - 1 == test_summary['degrees of freedom']
ttest_mu = tTest(y1=sal_a, mu=100000)
test_mu_summary = ttest_mu._generate_result_summary()
assert_almost_equal(test_mu_summary['Sample 1 Mean'], np.mean(sal_a))
assert_almost_equal(test_mu_summary['p-value'], 0.0002159346891279501)
assert_almost_equal(test_mu_summary['t-statistic'], 3.776470249422699)
assert test_mu_summary['alternative'] == 'two-sided'
assert test_mu_summary['test description'] == 'One-Sample t-test'
assert test_mu_summary['mu'] == 100000
assert len(sal_a) - 1 == test_mu_summary['degrees of freedom']
def test_two_sample_students_test(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
sal_b = self.data.loc[self.data['discipline'] == 'B']['salary']
ttest = tTest(y1=sal_a, y2=sal_b, var_equal=True)
test_summary = ttest.test_summary
np.testing.assert_almost_equal(test_summary['Sample 1 Mean'],
np.mean(sal_a))
np.testing.assert_almost_equal(test_summary['Sample 2 Mean'],
np.mean(sal_b))
np.testing.assert_almost_equal(test_summary['t-statistic'],
-3.1485647713976195)
np.testing.assert_almost_equal(
test_summary['p-value'],
t.cdf(test_summary['t-statistic'],
test_summary['degrees of freedom']) * 2)
assert test_summary['alternative'] == 'two-sided'
assert test_summary[
'test description'] == "Two-Sample Student's t-test"
assert len(sal_a) + len(
sal_b) - 2 == test_summary['degrees of freedom']
def test_two_sample_welch_test(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
sal_b = self.data.loc[self.data['discipline'] == 'B']['salary']
ttest = tTest(y1=sal_a, y2=sal_b)
test_summary = ttest.test_summary
np.testing.assert_almost_equal(test_summary['Sample 1 Mean'],
np.mean(sal_a))
np.testing.assert_almost_equal(test_summary['Sample 2 Mean'],
np.mean(sal_b))
np.testing.assert_almost_equal(test_summary['t-statistic'],
-3.1386989278486013)
np.testing.assert_almost_equal(test_summary['degrees of freedom'],
377.89897288941387)
np.testing.assert_almost_equal(
test_summary['p-value'],
t.cdf(test_summary['t-statistic'],
test_summary['degrees of freedom']) * 2)
assert test_summary['alternative'] == 'two-sided'
assert test_summary['test description'] == "Two-Sample Welch's t-test"
ttest_group = tTest(group=self.data['discipline'],
y1=self.data['salary'])
test_group_summary = ttest_group.test_summary
np.testing.assert_almost_equal(test_summary['Sample 1 Mean'],
test_group_summary['Sample 1 Mean'])
np.testing.assert_almost_equal(test_summary['Sample 2 Mean'],
test_group_summary['Sample 2 Mean'])
np.testing.assert_almost_equal(test_summary['p-value'],
test_group_summary['p-value'])
np.testing.assert_almost_equal(
test_summary['degrees of freedom'],
test_group_summary['degrees of freedom'], 5)
np.testing.assert_almost_equal(test_summary['t-statistic'],
test_group_summary['t-statistic'])
assert test_group_summary['alternative'] == 'two-sided'
assert test_group_summary[
'test description'] == "Two-Sample Welch's t-test"
def test_alternatives(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
sal_b = self.data.loc[self.data['discipline'] == 'B']['salary']
ttest = tTest(y1=sal_a, y2=sal_b, alternative='greater')
test_summary = ttest.test_summary
assert_almost_equal(test_summary['p-value'], 0.9990848459959981)
assert_almost_equal(test_summary['t-statistic'], -3.1386989278486013)
assert test_summary['alternative'] == 'greater'
ttest_less = tTest(y1=sal_a, y2=sal_b, alternative='less')
test_less_summary = ttest_less.test_summary
assert test_less_summary['alternative'] == 'less'
assert_almost_equal(test_less_summary['t-statistic'],
-3.1386989278486013)
assert_almost_equal(test_less_summary['p-value'],
0.0009151540040019292)
def test_ttest_exceptions(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
sal_b = self.data.loc[self.data['discipline'] == 'B']['salary']
with pytest.raises(ValueError):
tTest(y1=sal_a, paired=True)
with pytest.raises(ValueError):
tTest(y1=sal_a, y2=sal_b, paired=True)
with pytest.raises(ValueError):
tTest(sal_a, sal_b, alternative='asdh')
with pytest.raises(ValueError):
tTest(group=self.multiclass_data['spray'],
y1=self.multiclass_data['count'])
def test_paired_sample_test(self):
sal_a = self.data.loc[self.data['discipline'] == 'A']['salary']
sal_b = self.data.loc[self.data['discipline'] == 'B']['salary']
sal_b2 = sal_b[0:len(sal_a)]
ttest = tTest(y1=sal_a, y2=sal_b2, paired=True)
test_summary = ttest.test_summary
assert_almost_equal(test_summary['Sample Difference Mean'],
np.mean(np.array(sal_a) - np.array(sal_b2)))
assert_almost_equal(test_summary['t-statistic'], -2.3158121700626406)
assert_almost_equal(
test_summary['p-value'],
t.cdf(test_summary['t-statistic'],
test_summary['degrees of freedom']) * 2)
assert test_summary['alternative'] == 'two-sided'
assert test_summary['test description'] == 'Paired t-test'
assert len(sal_a) - 1 == test_summary['degrees of freedom']
