Lecture 1: IntroductionLecture 2: Basics of probabilityLecture 3: Regression and GraphsLecture 4: Potential OutcomesLecture 5: Potential outcomes, propensity scoreLecture 6: Instrumental variablesLecture 7: Sensitivity AnalysisLecture 8: Difference in differenceLecture 9: Pearl's do operatorLecture 10: The adjustment formula (Pearl)Lecture 11: Front doorLecture 12: PC algorithmLecture 13: Do_calculus_optimal_conditioningLecture 14: Mediation part 1Lecture 15: CounterfactualLecture_16_17: Counterfactuals, attribution, mediationLecture 18: ANMsRevision summary slides License All rights reserved The University of Edinburgh Book traversal links for MCI: Lecture Slides MCI: Methods for Causal Inference Up MCI: Resource List