Causality in the Sciences

Causality in the Sciences
Author: Phyllis McKay Illari
Publisher: Oxford University Press
Total Pages: 953
Release: 2011-03-17
Genre: Mathematics
ISBN: 0199574138

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Why do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences.


Causality in the Sciences
Language: en
Pages: 953
Authors: Phyllis McKay Illari
Categories: Mathematics
Type: BOOK - Published: 2011-03-17 - Publisher: Oxford University Press

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Why do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inferen
Time and Causality Across the Sciences
Language: en
Pages: 273
Authors: Samantha Kleinberg
Categories: Computers
Type: BOOK - Published: 2019-09-26 - Publisher: Cambridge University Press

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Explores the critical role time plays in our understanding of causality, across psychology, biology, physics and the social sciences.
Causality and Causal Modelling in the Social Sciences
Language: en
Pages: 236
Authors: Federica Russo
Categories: Social Science
Type: BOOK - Published: 2008-09-18 - Publisher: Springer Science & Business Media

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This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued tha
Mechanism and Causality in Biology and Economics
Language: en
Pages: 256
Authors: Hsiang-Ke Chao
Categories: Philosophy
Type: BOOK - Published: 2013-07-31 - Publisher: Springer Science & Business Media

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This volume addresses fundamental issues in the philosophy of science in the context of two most intriguing fields: biology and economics. Written by authoritie
The Book of Why
Language: en
Pages: 432
Authors: Judea Pearl
Categories: Computers
Type: BOOK - Published: 2018-05-15 - Publisher: Basic Books

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A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intell