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The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence .
Author: Judea Pearl
Publisher: Cambridge University Press
ISBN: 9780521895606
Category: Computers
Page: 464
View: 307
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,...JUDEA PEARL - HOME
HOMEPUBLICATIONSBIOCAUSALITYPRIMERWHYDANIEL PEARL FOUNDATION
Welcome to my homepage.
To find out what I am up to, new submissions, working papers, adventures and introspections, click here.
For discussions and disputations concerning controversial topics read the Causality Blog.
To view the slides of my tutorial at the Joint Statistical Meetings (JSM-16), Chicago, IL, August 1, 2016, click [ppt] or [pdf].
To view my commencement speech at the University of Toronto June 21, 2007, click here.For transcript, click here.
For a gentle introduction to my current research on causality, [click 1 or 2].
Transcript and slides of 1996 Faculty Research Lecture: The Art and Science of Cause and Effect
Transcript and slides of 1999 IJCAI Award Lecture: Reasoning with Cause and Effect
Causality Download Free Version
Technical material supporting the story in 1-2, can be found [postscript] or [pdf] in:
- (R-350): [pdf]
J. Pearl, 'Causal inference in statistics: An overview,' Statistics Surveys, 3:96--146, 2009. - (R-264): [pdf]
J. Pearl, ``Simpson's paradox: An anatomy' Extracted from Chapter 6 of CAUSALITY. - (R-218-B): [postscript][pdf]
J. Pearl, 'Causal Diagrams for Empirical Research' Biometrika, 82(4), 669--710, December 1995.
Key publications related to causality
Causality download free. full
- (R-320):[postscript][pdf]
J. Pearl, 'Robustness of Causal Claims' In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, AUAI Press: Arlington, VA, 446-453, July 2004. - (R-290):[pdf]
J. Tian and J. Pearl, 'A General Identification Condition for Causal Effects' In Proceedings of the Eighteenth Conference on Artificial Intelligence, AAAI/The MIT Press: Menlo Park, 567-573, August 2002. - (R-273-U): [postscript][pdf]
J. Pearl, 'Direct and Indirect Effects' In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 411-420, 2001. - (R-266-Part1):[pdf]
J.Y. Halpern and J. Pearl, 'Causes and explanations: A structural-model approach- -- Part I: Causes' In British Journal of Philosophy of Science, 56:843-887, 2005.
- (R-266-Part2): [pdf]
J.Y. Halpern and J. Pearl, 'Causes and explanations: A structural-model approach- -- Part II: Explanations' In British Journal of Philosophy of Science, 56:889-911, 2005.
- (R-269): [postscript][pdf]
J. Pearl, 'The logic of counterfactuals in causal inference (Discussion of `Causal inference without counterfactuals' by A.P. Dawid),' In Journal of American Statistical Association, Vol. 95, No. 450, 428--435, June 2000. - (R-271-A): [postscript][pdf]
J. Tian and J. Pearl, 'Probabilities of causation: Bounds and identification' In Annals of Mathematics and Artificial Intelligence, Vol. 28, 287--313, 2000.