Analyze A/B Test Results

Introduction

A/B tests are very commonly performed by data analysts and data scientists.

In this project, work is done 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 through the analysis report so that they are able to make their decision.

To achieve the goal, as mentioned above, heavy use of practical statistics is done in most of the report to place emphasis on the analysis part of the data analysis process.

Softwares needed:

You will need an installation of Python, plus the following libraries:

1. pandas
2. NumPy
3. Matplotlib

• A text editor, like VS Code or Atom.
• A terminal application (Terminal on Mac and Linux or Cygwin on Windows).

Installation links for softwares:

• Git for windows - for terminal application using Git Bash
• Python using Anaconda (latest version for windows)
• Visual Studio Code Editor (for windows)

Resources

1. Logistic Regression Classifier
2. Why Bootstrapping Works