This is an A/B testing assignment completed for Udacity's Data Analyst Nano Degree Program. The project consisted of understanding the results of an A/B test run by an e-commerce website and helping the company understand through statistical conclusions, if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.

Steps will include handling mismatched condition and page assignment, removing duplicate ids, hypothesis testing via standard statistical tests, and multiple regression modelling.

To complete this project, I will require the following softwares:

• Python (Numpy, Pandas, Matplotlib, StatsModels)
• Jupyter Notebook (for running files)

• Try to find probability of an individual receiving the new page or an old page and what are the chances of those.