This project was completed as a part of Udacity's Data Science Nanodegrees and consists of the following three parts:

Part I - Probability

Part II - A/B Test

Part III - Regression

It analyses conversion of users on a website, sets and tests a hypothesis, visualizes the results with matplotlib and uses statsmodels and scipy to evaluate the results.

Finally, by using statsmodels we fit a regression model to see if there is a significant difference in conversion based on which page customers receive.

Libraries used:

pandas

numpy

random

matplotlib.pyplot

statsmodels.api