Causality Models Reasoning and Inference 2nd Edition by Judea Pearl‎ 052189560X 978-0521895606

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ISBN-10 ‏ : ‎ 052189560X

ISBN-13 ‏ : ‎ 978-0521895606

Author:  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, 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. The book will open the way for including causal analysis in the standard curricula of statistics, artificial intelligence, business, epidemiology, social sciences, and economics. Students in these fields will find natural models, simple inferential procedures, and precise mathematical definitions of causal concepts that traditional texts have evaded or made unduly complicated. The first edition of Causality has led to a paradigmatic change in the way that causality is treated in statistics, philosophy, computer science, social science, and economics. Cited in more than 5,000 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 interests to students and professionals 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.

 

Causality Models Reasoning and Inference 2nd Table of contents:

 

1. Preface

2. 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)

3. Reviews
     5.1 Preliminary Reviews
     5.2 Journal Reviews

4. Discussion with readers
     6.1 Corrections to 2nd Edition

5. Viewgraphs and homeworks for instructors

6. Recent seminars

Video of lecture on causes and counterfactuals
Tutorial (December, 2013), “Causes and Counterfac tuals: Concepts, Principles and Tools,” click here.
Lecture (April, 2013), “The Mathematics of Causal Inference: With Reflections on Machine Learning,” click here.
For videos (July, 2011), including a Lecture, a symposium, and an interview, click here.

7. Lakatos Award for 2001

8. Excerpts from the 2nd edition of Causality
(Cambridge University Press, 2009)
Also includes Errata for 2nd edition.

 

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