36-431 Foundations of Causal Inference

6 units, Carnegie Mellon University

This course will provide an introduction to the fundamentals of causal inference. Causal inference is concerned with whether and how one can go beyond statistical associations to draw causal conclusions from observational data. Topics will include counterfactuals potential outcomes and graphs, identification and estimation of average treatment effects in experiments and observational studies, nonparametric bounds, sensitivity analysis, instrumental variables, effect modification, and longitudinal studies. Special permission is required for undergraduate students.

Prerequisites: none listed

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