Causality : models, reasoning, and inference
Judea Pearl (Author)
"Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science and the health and social sciences. The author presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation, and he devises simple mathematical tools for studying the relationships between causal connections and statistical associations. The book will open the way for including causal analysis in the standard curricula of statistics, artificial intelligence, business, epidemiology, social science, and economics. Students in these areas will find natural models, simple inferential procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. Causality will be of interest to students and professionals in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable."--front flap
Print Book, English, 2000
Cambridge University Press, Cambridge, U.K., 2000