Metadata-Version: 2.4
Name: mcab
Version: 0.1.0
Summary: Monte Carlo A/B Testing Library - comprehensive tools for A/B test design and analysis
Author: Sergey Lastochkin
License: MIT
Project-URL: Homepage, https://github.com/sslastochkin/mcab
Project-URL: Documentation, https://sslastochkin.github.io/mcab/
Project-URL: Repository, https://github.com/sslastochkin/mcab
Project-URL: Bug Tracker, https://github.com/sslastochkin/mcab/issues
Keywords: ab-testing,monte-carlo,statistics,hypothesis-testing,experimentation,data-science,bootstrap,permutation-test,multiple-testing,experiments
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.20.0
Requires-Dist: pandas>=1.3.0
Requires-Dist: scipy>=1.7.0
Requires-Dist: matplotlib>=3.4.0
Requires-Dist: seaborn>=0.11.0
Requires-Dist: joblib>=1.0.0
Requires-Dist: tqdm>=4.60.0
Requires-Dist: threadpoolctl>=3.0.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Requires-Dist: pytest-cov>=3.0.0; extra == "dev"
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Provides-Extra: docs
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Requires-Dist: sphinx-rtd-theme>=1.0.0; extra == "docs"
Requires-Dist: numpydoc>=1.2.0; extra == "docs"
Dynamic: license-file

# MCAB: Monte Carlo Simulations for A/B Testing
A Python toolkit to design and validate A/B experiments via simulation: estimate power, find MDE, and control type-I error. Supports iid &amp; ratio metrics, linearization, CUPED/CUPAC variance reduction, bootstrap/permutation tests, multiple-testing corrections, and AA/AB benchmarking.
