printer friendly pageSTATS 209: Introduction to Causal Inference
This course introduces the fundamental ideas and methods in causal inference, with examples drawn from education, economics, medicine, and digital marketing. Topics include potential outcomes, randomization, observational studies, matching, covariate adjustment, AIPW, heterogeneous treatment effects, instrumental variables, regression discontinuity, and synthetic controls. Prerequisites:
STATS116/118,
STATS 191/203. See
https://statistics.stanford.edu/course-equiv for equivalent courses in other departments that satisfy these prerequisites.
Last offered: Autumn 2023
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