A Python package for the statistical analysis of A/B tests
-
Updated
Jun 7, 2026 - Python
#
cuped
Here are 27 public repositories matching this topic...
因果推理&AB实验相关论文小书库
-
Updated
Mar 12, 2023
Causalis - State-of-the-art robust causal inference for experiments and observational data in python
python data-science machine-learning statistics ai dml rct econometrics experimentation ab-testing gate causal-inference synthetic-control uplift-modeling causalml pydantic difference-in-differences cuped double-machine-learning
-
Updated
Jun 9, 2026 - Python
Theory and implementatuon of various A/B experiments
-
Updated
Jun 9, 2020 - Jupyter Notebook
AB testing, stattests, poisson bootstrap, cuped, linearization
-
Updated
Apr 23, 2023 - Jupyter Notebook
Воспроизводимые эксперименты по снижению дисперсии оценки эффекта: plain diff, CUPED, VWE и их комбинация.
-
Updated
Apr 9, 2026 - Python
A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python
-
Updated
Sep 9, 2023 - Jupyter Notebook
896 tests / 42 scripts validating Zetyra calculators (GSD, CUPED, Bayesian, SSR incl. Single-Arm, RAR, Master Protocol). Replicates 8 published trials (Salk, DAPA-HF, PACIFIC, MONALEESA-7, I-SPY 2, STAMPEDE, REMAP-CAP, NCT03377023) + Leyrat 2024.
python r validation monte-carlo fda biostatistics clinical-trials bayesian sample-size oncology adaptive-design prior-elicitation cuped group-sequential-designs basket-trial master-protocol statistical-validation bayesian-toolkit platform-trial nct03377023
-
Updated
May 15, 2026 - Python
Тыкаюсь в темах интенсива A/B-week от ШАДа
-
Updated
Aug 13, 2025 - Jupyter Notebook
An end-to-end A/B testing program review: 6 experiments, 2 ships, and the decision-quality framework behind them
-
Updated
Apr 15, 2026 - Jupyter Notebook
A Python package for the full A/B test lifecycle, from power analysis to sequential monitoring and variance reduction
-
Updated
May 18, 2026 - Python
End-to-end A/B experimentation toolkit: experiment readouts, MDE & power calculations, CUPED variance reduction, and decision-focused reporting in a Big Tech economist style.
python econometrics experimentation ab-testing causal-inference mde power-analysis cuped big-tech-economist
-
Updated
Jan 14, 2026 - HTML
End-to-end A/B testing framework — power analysis, SRM checks, CUPED variance reduction, BH-corrected segment breakouts, and an auto-generated ship/no-ship decision doc. Built on a 60k-user synthetic checkout experiment.
python bootstrap data-science statistics experimentation data-analysis ab-testing hypothesis-testing statsmodels causal-inference power-analysis cuped
-
Updated
May 22, 2026 - Python
End-to-end analysis of a three-arm RCT with hypothesis testing, power analysis, segmentation, CUPED variance reduction, and causal inference.
experimentation ab-testing hypothesis-testing causal-inference power-analysis cuped propensity-score-matching
-
Updated
Apr 28, 2026 - Jupyter Notebook
A/B testing project comparing difference-in-means vs CUPED on the Hillstrom email experiment.
-
Updated
May 7, 2026 - Jupyter Notebook
Modern A/B experimentation utilities: CUPED/CUPAC hooks, triggered analysis, SRM, switchback helpers, and power sims.
python statistics experimentation ab-testing srm causal-inference variance-reduction power-analysis cuped switchback
-
Updated
Apr 17, 2026 - Python
Experimentation and causal inference platform for product decision systems, implementing A/B testing, CUPED variance reduction, and Difference-in-Differences analysis with reproducible pipelines.
ab-testing causal-inference product-analytics difference-in-differences experimentation-platform cuped
-
Updated
Feb 20, 2026 - Jupyter Notebook
Local-first experimentation and causal decision platform for A/B testing, CUPED, trust checks, segment-aware rollout policy, and simulation-driven validation.
python simulation experimentation ab-testing causal-inference uplift-modeling fastapi streamlit feature-evaluator cuped duckdb
-
Updated
May 17, 2026 - Python
Production A/B testing framework with Budget A/B, CUPED variance reduction, and sequential testing - DoorDash methodology
-
Updated
Feb 1, 2026 - Python
Production-simulated experimentation, metrics intelligence, CUPED/guardrail decisioning, and streaming observability platform.
streaming metrics experimentation ab-testing data-quality decision-science anomaly-detection product-analytics fastapi cuped
-
Updated
May 16, 2026 - Python
Improve this page
Add a description, image, and links to the cuped topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the cuped topic, visit your repo's landing page and select "manage topics."