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Causality : models, reasoning, and inference

โœ Scribed by Pearl, Judea


Publisher
Cambridge University Press
Year
2000
Tongue
English
Leaves
394
Edition
1ed.
Category
Library

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โœฆ Synopsis


Written by one of the pre-eminent 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, philosophy, cognitive science, and the health and social sciences. 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, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students 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. Professor of Computer Science at the UCLA, Judea Pearl is the winner of the 2008 Benjamin Franklin Award in Computers and Cognitive Science

โœฆ Table of Contents


Content: Introduction to probabilities, graphs, and causal models --
Theory of inferred causation --
Causal diagrams and the identification of causal effects --
Actions, plans, and direct effects --
Causality and structural models in social science and economics --
Simpson's paradox, confounding, and collapsibility --
Logic of structure-based counterfactuals --
Imperfect experiments: bounding effects and counterfactuals --
Probability of causation: interpretation and identification --
Actual cause.


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