Causal Inference (Part III, Michaelmas 2020)

This is a 16-lecture course on causal inference, the statistical science of drawing causal conclusions from experimental and non-experimental data.

Table of Contents

General information

  • Course syllabus.
  • Time: Tuesday & Thursday, 11am–12.
  • Location: Live-stream via Zoom (link available in Moodle).
  • Office hour: I will stay on Zoom after each lecture to answer questions. I would also like to chat with every Part III student who is taking this course. Please sign up here for a 20 minute slot.
  • Please email me if you find any mistakes or have any suggestions.


Number Date Topic Optional Reading
Part 1 Motivations
L1 <2020-10-08 Thu> Principles of causal inference Pearl Epilogue
L2 <2020-10-13 Tue> Potential outcomes and Neyman’s inference IR 1, 4, 6
L3 <2020-10-15 Thu> Randomisation test, regression adjustment IR 5, 7
L4 <2020-10-20 Tue> Regression adjustment; Linear SEM and path analysis Pearl 5.1
L5 <2020-10-22 Thu> Path analysis, correlation versus causation Review paper by Pearl
L6 <2020-10-27 Tue> Identification and estimation in linear SEMs A psychology paper
L7 <2020-10-29 Thu> Graphical models and Markov properties
L8 <2020-11-03 Tue> Structure discovery; Nonparametric SEMs Talk on SWIGs
L9 <2020-11-05 Thu> Single world intervention graphs; g-formula
L10 <2020-11-10 Tue> Causal identification HR 6
L11 <2020-11-12 Thu> No unmeasured confounders: Randomisation inference SSRMP tutorial slides
L12 <2020-11-17 Tue> Sensitivity analysis; Intro to semiparametric inference Review paper by Kennedy
L13 <2020-11-19 Thu> No unmeasured confounders: Semiparametric inference
L14 <2020-11-24 Tue> Doubly robust estimator; Leveraging specificity
L15 <2020-11-26 Thu> Instrumental variables
L16 <2020-12-01 Tue> Mediation analysis

Full Lecture notes (Last updated: December 16, 2020).

Lecture recordings can be found in Moodle.

Example classes


The following books/articles are optional. I am providing a short (personal) verdict to help you navigate the literature.

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