def test_t_test_welch(data_extra_info):
import numpy as np
df = data_extra_info.get_data()
t1 = df['Sample Type'].unique()[0]
t2 = df['Sample Type'].unique()[1]
g1 = np.array(df[df['Sample Type'] == t1]['volume'])
g2 = np.array(df[df['Sample Type'] == t2]['volume'])
perform_t_test(g1, g2, equal_var=False)
def test_baysian_hypothesis_test(data_extra_info):
import numpy as np
df = data_extra_info.get_data()
t1 = df['Sample Type'].unique()[0]
t2 = df['Sample Type'].unique()[1]
g1 = np.array(df[df['Sample Type'] == t1]['volume'])
g2 = np.array(df[df['Sample Type'] == t2]['volume'])
trace, s = baysian_hypothesis_test(g1, g2, t1, t2)
def test_test_normality(data_extra_info):
check_normality(data_extra_info.get_data()['volume'])
def test_box_cox_data(data_extra_info):
box_cox_data(data_extra_info.get_data().loc[:, atts].values)
def test_plot_histogram_as_dataframe(data_extra_info):
plot_histogram(data_extra_info.get_data(), 'volume')
def test_plot_qqplot(data_extra_info):
plot_qqplot(data_extra_info.get_data()['volume'])
def test_plot_boxplot_as_dataframe(data_extra_info):
plot_boxplot(data_extra_info.get_data(), 'volume')