6. A company is testing two versions of a webpage (A and B) to determine which version leads to more sales. Version A was shown to 1,000 users and resulted in 120 sales. Version B was shown to 1,200 users and resulted in 150 sales. Perform an A/B test to determine if there is a statistically significant difference in the conversion rates between the two versions. Use a 5% significance level.
PROGRAM:
import numpy as np
from statsmodels.stats.proportion import proportions_ztest
# Given data
successes = np.array([120, 150]) # number of sales for A and B
n = np.array([1000, 1200]) # number of users for A and B
alpha = 0.05 # significance level
# Perform two-proportion z-test
z_stat, p_value = proportions_ztest(successes, n)
# Print results
print(f"Z-statistic: {z_stat:.3f}")
print(f"P-value: {p_value:.5f}")
# Conclusion
if p_value < alpha:
print("Reject the null hypothesis: There is a significant difference in conversion rates between A and B.")
else:
print("Fail to reject the null hypothesis: No significant difference in conversion rates between A and B.")OUTPUT:
Z-statistic: -0.356
P-value: 0.72193
Fail to reject the null hypothesis: No significant difference in conversion rates between A and B.