A/B tests are very commonly performed by data analysts and data scientists. It is important that one get some practice working with the difficulties of these.
For this project, I work to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product. The goal is to work through this notebook and help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.