For this project, we work to understand the results of an A/B test run by an e-commerce website. The goal is 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.
Tools used:
- Python
- Jupyter Notebook
- pandas
- random
- matplotlib.pyplot
- statsmodels
Sections
- Part I - Probability & Descriptive Statistics
- Part II - A/B Test
- Part III - Regression Analysis