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
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  • 9.5 X 6.6 X 0.6 in
  • 156
  • Wiley
  • January 25, 2016
  • eng
  • 9781119186854
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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