AB Testing

This is a collection of AB testing methodologies and case studies.

Project 1: Analyze_AB_testing_Result

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

Project Objective:

• An e-commerce company has developed a new web page in order to increase the number of "converted" users - users who make purchases on the website.

• The goal of this project is to understand the results of an A/B test on their new and old websites and provide statistical and practical interpretation on the test results.

Analytical Scope:

• Sampling simulation and visulization
• Inferential Statistics: t-test, z-score and p-value
• Logistic regression

Data:

• ab_data.csv
• countries.csv

Document:

• Jupyter notebook: Analyze_AB_Test_Results.ipynb

Project 2: AB Testing Using Chi-square

This is a walk through of the tutorial on Chi-squared testing, based on randomly generated demographic data.

Analytical Scope:

• Chi-squared testing (one-dimensional table)
• Chi-squared testing of independence (two-dimensional table)

Document:

• Jupyter notebook: Chi-squared_ab_testing.ipynb
• Reference: Python for Data Analysis: Chi-Squared Tests

Project 3: Analysis of Variance (ANOVA)

This is a walk through of the tutorial on ANOVA testing, based on randomly generated demographic data.

Analytical Scope:

• One-way ANOVA
• Post-hoc testing
• Bonferroni correction
• Tukey test

Document:

• Jupyter notebook: Analysis_of_Variance (ANOVA).ipynb
• Reference: Python for Data Analysis: Analysis of Variance