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Tools and notebooks for causal inference, A/B testing, and experimentation - built for practitioners.

PyDay-BCN-2025

Causal Inference: a brief introduction | Discover how causal inference separates correlation from causation to drive better decisions. This fast-paced introduction covers key concepts—treatments, counterfactuals, DAGs, confounding, tests vs. observational data and tools like A/B tests and a real case with DiD and Synthetic Control Methods (SCM).

8Jupyter NotebookUpdated recently

Pricing-Experimentation-Causal-Inference

Análisis de pricing con inferencia causal usando Synthetic Control para estimar el impacto de cambios de precio y construir contrafactuales a nivel de mercado.

3Jupyter NotebookUpdated recently

bayesian-ab-api

No description available

1PythonUpdated recently

LLM-benchmarking-abtest-analysis

Benchmarking (Claude, Google Gemini and ChatGPT): analyzing AB test data with LLMs

Jupyter NotebookUpdated 1 month ago

Bayesian-AB-Test-Calculator

Simple Bayesian AB Test Calculator

4Jupyter NotebookUpdated 5 months ago

ubaldohervas.github.io

No description available

ab-testingcausal-inferencedata-scienceonline-experimentationstatistics
Updated 6 months ago

DiD-Calculator

DiD calculator with DoubleML library

1Jupyter NotebookUpdated 6 months ago

MDE-calculator-AB-test

MDE calculator for AB testing projects to calculate your sample size properly.

ab-testab-testingab-testing-analysisstatisticsstats
1Jupyter NotebookUpdated 8 months ago

sql-mysteries

Inspired by @veltman's command-line mystery, use SQL to research clues and find out whodunit!

Updated 3 years ago

GA4_API_python

No description available

Updated 3 years ago