Name: Causality
ISBN: 9780521895606

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Causality

Judea Pearl

Hardcover

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Do you recommend this book?

Yes!

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. The book will open the way for including causal analysis in the standard curricula of statistics, artificial intelligence, business, epidemiology, social sciences, and economics. Students in these fields will find natural models, simple inferential procedures, and precise mathematical definitions of causal concepts that traditional texts have evaded or made unduly complicated. The first edition of Causality has led to a paradigmatic change in the way that causality is treated in statistics, philosophy, computer science, social science, and economics. Cited in more than 5,000 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 interests 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.

Book Details

Publisher: Cambridge University Press
Publish Date: Sep 14th, 2009
Pages: 484
Language: English
Edition: undefined - 0002
Dimensions: 10.48in - 7.52in - 1.12in - 2.24lb
EAN: 9780521895606
Categories: • Philosophy & Social Aspects• Epistemology

About the Author

Pearl, Judea: - 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.

More books by Judea Pearl

Book Cover for: The Book of Why: The New Science of Cause and Effect, Judea Pearl

Book Cover for: Causal Inference in Statistics: A Primer, Judea Pearl

Book Cover for: An Introduction to Causal Inference, Judea Pearl

Book Cover for: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Judea Pearl

What people are saying

Steven Pinker

@sapinker

3 years

Cognitive scientist at Harvard.

Congratulations to AI expert and causality theorist Judea Pearl for winning The Frontiers of Knowledge Award. "for laying the foundations of modern artificial intelligence, so computer systems can process uncertainty and relate causes to effects" https://t.co/WOxao10fdD

🐣 tweets a bit 📚 stuff I've read 👀 mostly lurks ❤️ likes/follows interesting stuff/accounts 📷 active on instagram ⚠️ beware the algorithm ⚠️

read The Book of Why by @yudapearl. I think it might be the trailer for his textbook Causality: Models, Reasoning and Inference. And it's done its job. Flying the flag for reuniting meaning and method in maths… paying back over a century of technical debt. Wow! #crispinreads2022 https://t.co/fXSripvtSl

Alien from the future on a mission to enhance, extend & explore existence with AI.

@WiringTheBrain By the way, Kevin. I recommend you check out @SDMumford's & @ranilillanjum's work: https://t.co/vW5mtteExe Getting Causes from Powers. It's the sort of work relevant to our pursuit and gives you what you won't get from, Judea Pearl's accounts of causality.

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Praise for this book

"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

What people are saying

Steven Pinker

@sapinker

3 years

Cognitive scientist at Harvard.

🐣 tweets a bit 📚 stuff I've read 👀 mostly lurks ❤️ likes/follows interesting stuff/accounts 📷 active on instagram ⚠️ beware the algorithm ⚠️

twitter.com