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11

Causality

Causal Inference and Graphical Models

Causal graphs, do-calculus, potential outcomes, and experimental design.

Lessons

11.1

Potential Outcomes Framework

11.2

Directed Acyclic Graphs

11.3

Identifiability and the Backdoor Criterion

11.4

Randomized Experiments

11.5

Observational Studies and Treatment Effect Estimation

11.6

Policy Evaluation and Structural Identification

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