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    Causality: Models, Reasoning and Inference (Hardback) By (author) Judea Pearl

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    DescriptionWritten 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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  • Full bibliographic data for Causality

    Title
    Causality
    Subtitle
    Models, Reasoning and Inference
    Authors and contributors
    By (author) Judea Pearl
    Physical properties
    Format: Hardback
    Number of pages: 484
    Width: 180 mm
    Height: 257 mm
    Thickness: 30 mm
    Weight: 1,021 g
    Language
    English
    ISBN
    ISBN 13: 9780521895606
    ISBN 10: 052189560X
    Classifications

    B&T Book Type: NF
    BIC E4L: SCI
    Nielsen BookScan Product Class 3: S7.0
    B&T Modifier: Region of Publication: 01
    BIC subject category V2: PDA
    B&T Modifier: Academic Level: 01
    BIC subject category V2: JHBC, UYQ
    LC subject heading:
    BISAC V2.8: SCI075000
    Ingram Subject Code: SE
    B&T General Subject: 710
    LC classification: Q
    B&T Modifier: Text Format: 06
    Abridged Dewey: 501
    B&T Merchandise Category: UP
    LC subject heading:
    BIC subject category V2: PBB
    Warengruppen-Systematik des deutschen Buchhandels: 15220
    B&T Approval Code: A10302000
    DC22: 122
    LC classification: BD541 .P43 2000
    Thema V1.0: PDA
    Edition
    2
    Edition statement
    2nd ed.
    Illustrations note
    124 b/w illus. 7 tables
    Publisher
    CAMBRIDGE UNIVERSITY PRESS
    Imprint name
    CAMBRIDGE UNIVERSITY PRESS
    Publication date
    01 November 2009
    Publication City/Country
    Cambridge
    Author Information
    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.
    Review quote
    '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, reviews.com
    Table of contents
    1. Introduction to probabilities, graphs, and causal models; 2. A theory of inferred causation; 3. Causal diagrams and the identification of causal effects; 4. Actions, plans, and direct effects; 5. Causality and structural models in social science and economics; 6. Simpson's paradox, confounding, and collapsibility; 7. The logic of structure-based counterfactuals; 8. Imperfect experiments: bounding effects and counterfactuals; 9. Probability of causation: interpretation and identification; 10. The actual cause.