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Causal Inference in Statistics: A Primer

Judea Pearl, Madelyn Glymour, Nicholas P. Jewell




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 | #154692 in Books |  Pearl Judea |  2016-03-07 |  2016-02-19 | Original language:English | PDF # 1 |  9.70 x.30 x6.70l,.0 | File type: PDF | 160 pages

 | Causal Inference in Statistics A Primer

||1 of 1 people found the following review helpful.| The book is a "cause" for celebration!|By Tomas J Aragon|I teach R programming to epidemiologists at UC Berkeley. I have appreciated the explosion of data science. However, epidemiologist are not statisticians or computer scientists. Epidemiologists have a central role is understanding causal inference for protecting and promoting health. Graphical causal models (causal graphs

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, whi...

You can specify the type of files you want, for your gadget.Causal Inference in Statistics: A Primer   |  Judea Pearl, Madelyn Glymour, Nicholas P. Jewell. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.

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