causal-inference

Causal inference for data scientists and analysts — DAGs and do-calculus, propensity score methods, difference-in-differences, instrumental variables, regression discontinuity, synthetic control, and variance reduction techniques (CUPED), using CausalML, DoWhy, and rigorous A/B test analysis.