A/B tests are very commonly performed by data analysts and data scientists. For this project, we will be working to understand the results of an A/B test run by an e-commerce website. Our goal is to work through this notebook to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.
We used the following files provided by Udacity to work on this project:
These file contain the raw data for the control and experiment groups, what was their initial landing page, whether the opted for the new page or not and to which countries a particular user belongs.
Thanks to Udacity for teaching me Python 
