A/B Testing Analysis with Python

The A/B Testing Project aims to explore and analyze the effectiveness of a new
design variant compared to an existing one through rigorous statistical analysis and
experimentation. By leveraging user interaction data, the project seeks to uncover actionable
insights into various metrics such as completion rates, time spent on steps, error rates, and
abandonment rates. Through data preparation, exploration, analysis, and statistical testing using
Python libraries such as scipy and statsmodels, the project determines whether the proposed
design changes lead to meaningful improvements in user engagement and overall user
experience.