Causality
Causality
£54.99
GBPWritten 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.
- Presents the first unified account of the various approaches to causation
- Offers simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions, and observations
- Facilitates the incorporation of causal analysis as an integral part of the standard curricula in statistics, artificial intelligence, business, epidemiology, social science, and economics
- The author is the winner of the prestigious Technion Harvey Prize 2012, considered a good predictor of the Nobel Prize, 'in recognition of his foundational work that has touched a multitude of spheres of modern life'
Reviews & endorsements
'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.' 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, reviews.com
Product details
November 2009Hardback
9780521895606
484 pages
260 × 185 × 30 mm
1.07kg
124 b/w illus. 7 tables
Available
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 social science and economics
- 6. Simpson's paradox, confounding, and collapsibility
- 7. The logic of structure-based counterfactuals
- 8. Imperfect experiments: bounding effects and counterfactuals
- 9. Probability of causation: interpretation and identification
- 10. The actual cause.
