Get startedGet started for free

Mann-Whitney U test

Let's assume that you are an Analytics Engineer at an early-stage start-up where the traffic size to your website is small. Since in many cases you will need to run the tests for a long duration to gather a sample size that is large enough to satisfy parametric tests' assumptions, you may need to lean on non-parametric tests to make faster decisions.

One of these tests is the Mann-Whitney U test, which is a statistical significance test used to determine if two independent samples were drawn from a population with the same distribution. You will leverage this test to analyze the difference in time_on_page between two groups of the checkout dataset. The checkout DataFrame is available for you and pingouin has been loaded along with pandas and numpy.

This exercise is part of the course

A/B Testing in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate the mean and count of time on page by variant
print(checkout.____('checkout_page')['____'].____({'____', '____'}))
Edit and Run Code