AB_test_analysis

This is the third project done on Udacity's Data Analyst Nanodegree program, where I analyzed results of an A/B test run by an e-commerce website. My goal was to work through this notebook to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.

Getting started

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

• numpy
• pandas
• matplotlib.pyplot
• random
• scipy.stats
• statsmodels.api

Statistical analysis

• Bootstrapping sampling distributions and p-value calculations
• Z-core test
• Logistic regression
• Multiple linear regression

Key findings

• The conversion rate for the new page is not better than for the old page
• The country parameter of the user did not impact the conversion rate