Beyond Correlation: A Practical Guide to the Backdoor Criterion in Python
Estimating the effect of one variable on another is at the core of causal inference.
2025-12-16
Tutorials
Hands-on guides, code walkthroughs, and causal inference tutorials for data scientists.
Parallel Trends: The Make-or-Break Assumption for Difference-in-Differences
Difference-in-Differences (DiD) is a widely used technique to estimate causal effects when randomized experiments are
2025-06-21
Causal AI in Action: Drive Conversions with Uplift Modeling
In the world of marketing, deciding which customers to target with specific promotions can feel
2025-05-17
Causal Inference with Python: An Ultimate Guide to Propensity Score Matching
Evaluating the impact of treatments or interventions is critical in various fields, including business and
2024-07-02