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Causal Inference in Statistics - A Primer
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Causal Inference in Statistics - A Primer
von: Judea Pearl, Madelyn Glymour, Nicholas P. Jewell
Wiley, 2016
ISBN: 9781119186854
160 Seiten, Download: 2713 KB
 
Format:  PDF
geeignet für: Apple iPad, Android Tablet PC's Online-Lesen PC, MAC, Laptop

Typ: A (einfacher Zugriff)

 

 
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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.  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.



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 Statistics, University of California, Berkeley, USA



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