Resources

Books

“Causal Inference In Statistics — A Primer” by the GOAT Himself. Read this first.

Graphs

• Daggity: Old and New 🤩
  • Learn Graphs (and all sorts of other CI things) interactively.
  • Ancestors, Parents, Children, Descendants (do this!)
  • Covariates in DAGs (do this!)
  • Learn Covariates in DAGs

Videos

Many of these are introductory.

• Richard McElreath - Science Before Statistics: Causal Inference
  Three hours long but excellent.
• Jonas Peters - Mini Course on Causality at the Broad Institute, Parts One, Two, and Three
• Judea Pearl - The New Science of Cause and Effect
  The GOATed One Himself.
• What is Inference?
  Philosophical standpoint.

Other

• Sample Github Project for study/practice.

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About that $p^M$ mess: When you say $p^{M_d}(Y = y) = 0.75$, you’re saying “I subjectively believe that when the model takes decision $D=d$, I will see event $Y=y$.