Unlocking Causal Reasoning: A Beginner’s Guide to Graphical Models
This article introduces causal graphical models as a language for reasoning about cause‑and‑effect, explains key concepts such as conditional independence, colliders, back‑door paths, confounding and selection bias, and shows how to identify and adjust for bias using simple visual examples.