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FYI there's (at least?) two Judea Pearl books on causality. "Causality" was written in early 2000s, and is filled with theorems + proof + prose detailing all the major results from the theory. It's not a particularly hard book if you studied Mathematics, but it is Mathematics.

"Causal inference in statistics" is a 2017 book that covers the actually important results from the previous book, in an approachable manner, and with a focus on applying the results to actual problems. Some theorems are stated formally, but usually without proof. It's 40$ on Amazon, strongly recommended. https://www.amazon.com/Causal-Inference-Statistics-Judea-Pea...




There's also "The Book of Why", which is a pop-sci-ish book by Pearl and Dana Mackenzie. It contained just enough math and examples to get me really excited for causal inference, so I just bought "Causal inference in statistics" to see the theory in detail. If you want to learn what causal inference is about, but don't necessarily want to wade through a textbook immediately, I highly recommend "The Book of Why".

https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/0465...


If anyone's reading the first of those two, make sure to go straight to the last chapter or epilogue or whatever it was. IIRC, it's basically a talk turned into a chapter for the layman. This might only be the in the more recent edition(s).




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