Causality

Causality

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, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers’ questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.

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Description

Editorial Reviews

Review

“Make no mistake about it: This is an important book…. The field has no shortage of lively controversy and divergent opinion, but be that as it may, this is certainly one of the contributions that will bring this material further out of the closet and into the face of the broader statistical community, a move that we should welcome both as consumers and as testers of its utility.”
Journal of the American Statistical Association

“Pearl?s career has been motivated by problems of artificial intelligence, but the implications of this book are much broader. The distinctions he raises and the mathematical foundation he assembles are critical for every field of scientific endeavor. This updated edition of a modern classic deserves a broad and attentive audience.”
H. Van Dyke Parunak, Computing Reviews

“Pearl?s book is about probabilistic approaches to causality and it gives, especially, empirical researchers working with observational data an immense aid to their research. It also gives theoretical statisticians something to think about as it raises many issues of estimation for example in respective data generating processes. … This work of Pearl?s is an invaluable contribution to the current discussion on the topic of causal modeling. As described by the author his main objective of the book is to develop a framework that integrates substantive knowledge including counterfactuals (through new notations and concepts) with statistical data so as to refine the former and to interpret the latter.”
Priyantha Wijayatunga, Significance –This text refers to the hardcover edition.

About the Author

Judea Pearl is professor of computer science and statistics at the University of California, Los Angeles, where he directs the Cognitive Systems Laboratory and conducts research in artificial intelligence, human reasoning, and philosophy of science. The author of Heuristics and Probabilistic Reasoning, he is a member of the National Academy of Engineering and a Founding Fellow of the American Association for Artificial Intelligence. Dr Pearl is the recipient of the IJCAI Research Excellence Award for 1999, the London School of Economics Lakatos Award for 2001, and the ACM Alan Newell Award for 2004. In 2008, he received the Franklin Medal for computer and cognitive science from the Franklin Institute. –This text refers to the hardcover edition.

Book Description

Written by one of the preeminent researchers in the field, this provides a comprehensive exposition of modern analysis of causation. –This text refers to the hardcover edition.

Book Description

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. –This text refers to an out of print or unavailable edition of this title.

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Best Sellers Rank

#274,915 in Kindle Store (See Top 100 in Kindle Store) #92 in Probability & Statistics (Kindle Store) #433 in Science History & Philosophy #695 in Probability & Statistics (Books)

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