CommencerCommencer gratuitement

Checking for statistical significance

Now that you have an intuitive understanding of statistical significance and p-values, you will apply it to your test result data.

The four parameters needed for the p-value function are the two conversion rates - cont_conv and test_conv and the two group sizes - cont_size and test_size. These are available in your workspace, so you have everything you need to check for statistical significance in our experiment results.

Cet exercice fait partie du cours

Customer Analytics and A/B Testing in Python

Afficher le cours

Instructions

Find the p-value of our experiment using the loaded variables cont_conv, test_conv, cont_size, test_size calculated from our data. Then determine if our result is statistically significant by running the second section of code.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Compute the p-value
p_value = get_pvalue(con_conv=____, test_conv=____, con_size=____, test_size=____)
print(p_value)

# Check for statistical significance
if p_value >= 0.05:
    print("Not Significant")
else:
    print("Significant Result")
Modifier et exécuter le code