First Course in Causal Inference (Peng Ding)

Got something to say to this podcast? Send a voicemail, and you might hear yourself on the next episode! Series: Mathematics & Science · AI Books · Book deep dive A First Course in Causal Inference — Peng Ding Peng Ding introduces causal inference from a statistical perspective. The book explains the foundations needed to reason about causal effects rather than associations alone. Examples and applications draw on biostatistics and econometrics. Mathematical arguments are accompanied by exercises, data, and practical R code. The course assumes basic probability, statistical inference, and familiarity with regression. Publication source Explore: Mathematics & Science · AI & Computer Science Related episodes: Graph Theory (Diestel) · Lie Groups, Lie Algebras, and Representations (Brian Hall)