Advanced A/B Testing & Experimentation Platform

Developing statistical testing framework with proper power analysis and sequential testing.

PythonStatisticsSequential TestingPower Analysis

Project Overview

This project focuses on creating a comprehensive A/B testing platform that goes beyond basic statistical testing. The platform includes proper power analysis, sequential testing capabilities, and causal inference methods to ensure reliable and actionable experiment results for large-scale marketing experiments.

Key Features

Advanced statistical testing with proper power analysis
Sequential testing for early stopping
Multi-armed bandit optimization
Causal inference integration
Automated experiment design and sizing
Comprehensive result interpretation and reporting

Challenges

Ensuring statistical validity in sequential testing
Handling multiple testing corrections
Managing experiment interference and spillover
Scaling to high-traffic applications
Balancing statistical rigor with business speed

Solutions

Implemented alpha-spending functions for sequential testing
Created automated multiple comparison corrections
Developed interference detection and mitigation
Built high-performance experiment infrastructure
Designed flexible statistical frameworks for different use cases

View Source Code

Interested in the technical implementation? Check out the complete source code on GitHub.

View on GitHub