The Third T-Test

Let's review the plots for the 'Purchase' column of the control and test groups.

Levene's Test:


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# Import libraries
import pandas as pd
from scipy.stats import levene

# Read .csv files
df_control = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c3b98ad3-420d-403f-908d-6ab8facc3e28/ab_control.csv', delimiter=';')
df_test = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c3b98ad3-420d-403f-908d-6ab8facc3e28/ab_test.csv', delimiter=';')

# Do Levene's test 
statistic, p_value = levene(df_control['Purchase'], df_test['Purchase'])

# Print result of Levene's test
print('Statistic:', statistic)
print('p-value:', p_value)

# Determine whether the variances are similar
if p_value > 0.05:
  print('The variances of the two groups are NOT statistically different')
else:
  print('The variances of the two groups are statistically different')

Now perform a t-test for the 'Purchase' columns:

H₀: The mean values of the column do not differ between the groups.

Hₐ: The mean values of the column differ between the groups.


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# Import libraries
import pandas as pd
from scipy.stats import ttest_ind

# Read .csv files
df_control = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c3b98ad3-420d-403f-908d-6ab8facc3e28/ab_control.csv', delimiter=';')
df_test = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c3b98ad3-420d-403f-908d-6ab8facc3e28/ab_test.csv', delimiter=';')

# Select only the 'Purchase' columns
data_control = df_control['Purchase']
data_test = df_test['Purchase']

# Do T-Test 
statistic, p_value = ttest_ind(data_control, data_test, equal_var=True)

# Print result of T-test
print('Statistic:', statistic)
print('p-value:', p_value)

In this case, the p-value (0.350) is higher than the acceptable significance level (0.05), indicating that there is insufficient evidence to suggest that the mean values differ between the groups. Now it's your turn!

Everything was clear?

Section 4. Chapter 4