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StatTest-Pro: A/B Testing & Hypothesis Verification Engine

StatTest-Pro is an end-to-end A/B testing analysis framework designed for Product and Growth teams. It calculates required sample sizes, enforces statistical rigor by auto-detecting anomalies like Sample Ratio Mismatches (SRM), evaluates hypothesis tests, and auto-generates executive reports.

Features

  • Sample Size & Power Calculation: Compute minimum requirements pre-test based on MDE, Alpha, and Power.
  • Safety Invariants (SRM): Automatically check for Sample Ratio Mismatch via Chi-Square Goodness-of-Fit. Halts automatic evaluation if $p < 0.01$.
  • Statistical Evaluation: Welch's T-Test and Z-tests for proportional/continuous metrics, computing $p$-values and 95% Confidence Intervals.
  • Automated Reporting: Generates 1-page HTML/PDF summary reports with clear visual distributions and business recommendations.

Directory Structure

  • docs/ - Comprehensive project documentation.
  • stattest_pro/ - Core framework source code.
  • tests/ - Pytest suite validating statistical invariants.
  • notebooks/ - Interactive examples and use cases.

Quick Start

# Install the framework from PyPI
pip install stattest-pro

Or build from source:

git clone https://github.com/Bibek-Dhakal/StatTest-Pro.git
cd StatTest-Pro

# Install the framework locally
pip install -e .[dev,notebooks]

# Run the test suite
pytest

Check out the docs/usage.md guide for code examples, or view the interactive notebook in the notebooks/ directory. Once you run an evaluation, open the generated .html report in any web browser to view the final outcome.

License

MIT License. See LICENSE.

Metadata

Release files for stattest-pro 0.2.0

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