Causality: Models, Reasoning and Inference

New York: Cambridge University Press (2000)
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Abstract

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

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Citations of this work

Grounding in the image of causation.Jonathan Schaffer - 2016 - Philosophical Studies 173 (1):49-100.
Bayesian Cognitive Science, Unification, and Explanation.Stephan Hartmann & Matteo Colombo - 2017 - British Journal for the Philosophy of Science 68 (2).
Contrastive causation.Jonathan Schaffer - 2005 - Philosophical Review 114 (3):327-358.
Cause and Norm.Christopher Hitchcock & Joshua Knobe - 2009 - Journal of Philosophy 106 (11):587-612.

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