A-B testing is my submmited project of practical statistics in udacity's data analysis nanodegree program
A/B tests are very commonly performed by data analysts and data scientists.For this project, my job is to understand the results of an A/B test run by an e-commerce website. My 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.
I used pandas, numpy, random, matplotlib to do the analysis, and used jupyter notebook to run all the code.
I followed the project instraction step by step to calculate probablilty, set the null hypothese, ran an A-B test, visualization result .
This project is Hao Xu's Udacity Nanodegree project. The datasets and instractions are all from udacity.