Graphical Models and Inference - Lecture 13

This lecture discusses the fundamentals of causal interpretation of graphical models based on directed acyclic graphs. In particular it concentrates on intervention calculus and identifiability of causal effects from observational and experimental studies.

See for example my SemStat notes for a more complete treatment of the issues.



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Last updated: Monday, 21 November 2011Steffen L. Lauritzen