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  3. Causality
  • Cited by 5302
      • 2nd edition
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    • Publisher:
      Cambridge University Press
      Publication date:
      05 March 2013
      14 September 2009
      ISBN:
      9780511803161
      9780521895606
      DOI:
      https://doi.org/10.1017/CBO9780511803161
      Dimensions:
      (253 x 215 mm)
      Weight & Pages:
      1.07kg, 484 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Philosophy of Science, Statistical Theory and Methods, Statistics and Probability, Philosophy
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    Subjects:
    Philosophy of Science, Statistical Theory and Methods, Statistics and Probability, Philosophy
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    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, 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.

    Awards

    Winner of the 2011 ACM Turing Award for Transforming Artificial Intelligence

    Reviews

    '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.'

    Source: 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 Source: reviews.com

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    Contents

    Contents
    • 1 - Introduction to Probabilities, Graphs, and Causal Models
      pp 1-40
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