Causality Models, Reasoning, and Inference

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 and statistical associations. The book will facilitate the incorporation of causal analysis as an integral part of the standard curriculum in statistics, business, epidemiology, social science and economics. Causality will be of interest to professionals and students in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences.