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‘Without assuming much beyond elementary probability theory. Judea pearl’s book provides an attractive tour of recent work, in which he has played a central role, on causal models and causal reasoning. Due to his efforts, and that of a few others, a Renaissance in thinking and using causal concepts is taking place.’ Patrick Suppes, Center for the Study of Language and Information, Stanford University
‘Judea Pearl has come to statistics and causation with enthusiasm and creativity. his work is always thought provoking and worth careful study. This book proves to be no exception. Time and again I found myself disagreeing both with his assumptions and with his conclusions, but I was also fascinated by new insights into problems I thought I already understood well. This book illustrates the rich contributions Pearl has made to the statistical literature and to our collective understanding of models for causal reasoning.’ Stephen Fienberg, Maurice Falk University professor of Statistics and Social Science, Carnegie Mellon University
'The book is extremely well written, and while mathematically precise, provides a thought-provoking study of causality and its implications.' Computing Review
‘Judea Pearl has come to statistics and causation with enthusiasm and creativity. his work is always thought provoking and worth careful study. This book proves to be no exception. Time and again I found myself disagreeing both with his assumptions and with his conclusions, but I was also fascinated by new insights into problems I thought I already understood well. This book illustrates the rich contributions Pearl has made to the statistical literature and to our collective understanding of models for causal reasoning.’ Stephen Fienberg, Maurice Falk University professor of Statistics and Social Science, Carnegie Mellon University
'The book is extremely well written, and while mathematically precise, provides a thought-provoking study of causality and its implications.' Computing Review
Product Description
Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.
Inside This Book
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First Sentence
Causality connotes lawlike necessity, whereas probabilities connote exceptionality, doubt, and lack of regularity. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Causality connotes lawlike necessity, whereas probabilities connote exceptionality, doubt, and lack of regularity. Read the first page
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Concordance
Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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45% buy the item featured on this page: Causality: Models, Reasoning, and Inference £34.74 |
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25% buy Causality: Models, Reasoning and Inference |
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14% buy Causal Models: How People Think About the World and Its Alternatives£7.99 |
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8% buy Making Things Happen: A Theory of Causal Explanation (Oxford Studies in the Philosophy of Science) £14.68 |
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