This graduate-level sequence bridges the gap between statistical association and causal inference. Students explore pitfalls like Simpson's Paradox and collider bias while learning to use Directed Acyclic Graphs (DAGs) and Instrumental Variables to isolate causal mechanisms in bivariate data.