hpkolse / dand-a-b-testing

Analyze A/B Test Results : Project under Udacity's Data Analytics Nano Degree.

Analyze A/B Test Results.

This project was completed as part of the course requirements of Udacity's Data Analyst Nanodegree certification.

Overview

The project conducted A/B testing of user conversions on an old and new webpage.

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

To get evidence about results I have been applying the essential practical statistics including Probability, Bayes rule, A/B tests, Hypothesis testing, Sampling Distribution, Confidence Intervals And have been using a Machine Learning model (Logistic Regression Model) to build intuition about Individuals.

Python3 is the Kernel used to achieve the notebook, importing Pandas, Numpy, Matplotlib and Statmodels libraries.