Causality
Models, Reasoning, and Inference
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21 256 Ft
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Product details:
- Publisher Cambridge University Press
- Date of Publication 13 March 2000
- ISBN 9780521773621
- Binding Hardback
- No. of pages400 pages
- Size 264x187x28 mm
- Weight 895 g
- Language English
- Illustrations 110 b/w illus. 8 tables 0
Categories
Short description:
Causality offers the first comprehensive coverage of causal analysis in many sciences.
MoreLong 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.
'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
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 the social sciences; 6. Simpson's paradox, confounding, and collapsibility; 7. Structural and counterfactual models; 8. Imperfect experiments: bounds and counterfactuals; 9. Probability of causation: interpretation and identification; Epilogue: the art and science of cause and effect.
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