FAQ: Why Data? - Hypothesis Testing for A/B Tests

This community-built FAQ covers the “Hypothesis Testing for A/B Tests” exercise from the lesson “Why Data?”.

Paths and Courses
This exercise can be found in the following Codecademy content:

FAQs on the exercise Hypothesis Testing for A/B Tests

There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply (reply) below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply (reply) below!

Agree with a comment or answer? Like (like) to up-vote the contribution!

Need broader help or resources? Head here.

Looking for motivation to keep learning? Join our wider discussions.

Learn more about how to use this guide.

Found a bug? Report it!

Have a question about your account or billing? Reach out to our customer support team!

None of the above? Find out where to ask other questions here!

It would be interesting to delve deeper into the calculation of whether it was a success or not, I can tell the result is 0.000861041411367(so I can tell its a success). How does that all get put together though?

1 Like

I understand that we are testing for significance, but I would like to request a step by step what the code is doing.

How is ‘from scipy.stats import chi2_contingency’ affecting the variables? There isn’t even an over-simplified attempt to explain what this import does. :expressionless: Just copy/paste and click next. :frowning:

1 Like