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Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon.

— Judea Pearl

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More quotes by Judea Pearl

You cannot answer a question that you cannot ask, and you cannot ask a question that you have no words for.

The Book of Why (2018)

Data do not understand causes and effects; humans do.

The Book of Why (2018)

A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet.

A quantity Q(M) is identifiable, given a set of assumptions A, iffor any two models M1 and M2 that satisfy A, we have

Simpson's paradox (Simpson 1951; Blyth 1972), first encountered by Pearson in 1899 (Aldrich 1995), refers to the phenomenon whereby an event C increases the probability of E in a given population p and, at the same time, decreases the probability of E in every subpopulation of p.

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Quote text and notes from Wikiquote: Judea Pearl (page history), available under CC BY-SA 4.0. Source quality and labels are our own summary of what Wikiquote records.