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Causal Inference in Statistics

by Judea Pearl

2020-12-29 15:11:08

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Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Example... Read more
Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning. Less

Book Details

File size9.5 X 6.6 X 0.6 in
Print pages156
PublisherWiley
Publication date January 25, 2016
Languageeng
ISBN9781119186854
autor-image
Judea Pearl
Author
Judea Pearl, Computer Science and Statistics, University of California, Los Angeles, USA Madelyn Glymour, Philosophy, Carnegie Mellon University, Pittsburgh, USA Nicholas P. Jewell, Biostatistics and ...

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