This project was completed as part of Udacity's Advanced Data Analysis Nanodegree Program.
A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.
For this project, I will be working to understand the results of an A/B test run by an e-commerce website. The main 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.
- Bootstrapping sampling distributions
- P-value and Z-score calculation
- Logistic regression
- Pandas, Numpy, Matplotlib, StatsModels, Scipy