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Causality: Models, Reasoning, and Inference (2000; updated 2009) is a book by Judea Pearl. It is an exposition and analysis of causality. It is considered to have been instrumental in laying the foundations of the modern debate on causal inference in several fields including statistics, computer science and epidemiology.
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, ...
1. Why I wrote this book. 2. Table of Contents. 3. Preface 1st Edition 2nd Edition. 4. Preview of text. Epilogue: The Art and Science of Cause and Effect (from Causality, 2nd Edition) Important Topic: On the meaning of structural equations (from Causality, Sections 5.3.2 - 5.4.1) 5. Reviews 5.1 Preliminary Reviews 5.2 Journal Reviews. 6.
- Models, Reasoning, and Inference Second Edition
- Commendation for the First Edition
- Contents
- Preface to the First Edition
- Preface to the First Edition
Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causal-ity has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philoso-phy, cognitive science, ...
“Judea Pearl’s previous book, Probabilistic Reasoning in Intelligent Systems, was ar-guably the most influential book in Artificial Intelligence in the past decade, setting the stage for much of the current activity in probabilistic reasoning. In this book, Pearl turns his attention to causality, boldly arguing for the primacy of a notion long igno...
Preface to the First Edition Preface to the Second Edition
The central aim of many studies in the physical, behavioral, social, and biological sciences is the elucidation of cause–effect relationships among variables or events. However, the appropriate methodology for extracting such relationships from data – or even from the-ories – has been fiercely debated. The two fundamental questions of causality are...
fundamental building blocks both of physical reality and of human understanding of that reality, and I regard probabilistic relationships as but the surface phenomena of the causal machinery that underlies and propels our understanding of the world. Accordingly, I see no greater impediment to scientific progress than the prevailing practice of focu...
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13 de mar. de 2000 · In this book, Pearl turns his attention to causality, boldly arguing for the primacy of a notion long ignored in statistics and misunderstood and mistrusted in other disciplines, from physics to economics. He demystifies the notion, clarifies the basic concepts in terms of graphical models, and explains the source of many ...
- Judea Pearl
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
