# Causal Inference

> Distinguishing correlation from causation — RCTs, propensity scoring, instrumental variables, and causal ML.

![Status: developing](https://img.shields.io/badge/status-developing-yellow)

Open [`27-causal-inference.ipynb`](./27-causal-inference.ipynb) for learning objectives, prerequisites, and recommended reading order.

## Topics Covered

- Causal graphs (DAGs) and counterfactual reasoning
- RCTs, matching methods, and propensity score estimation
- Instrumental variables and regression discontinuity
- Causal machine learning and heterogeneous treatment effects

## Prerequisites

[02-data-science/README.md](../02-data-science/README.md) · [03-maths/README.md](../03-maths/README.md)

## What Comes Next

[28-practical-data-science/README.md](../28-practical-data-science/README.md)
