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Causal Inference in Statistics: A Primer by Madelyn Glymour, Nicholas P. Jewell, Judea Pearl (Paperback, 2016)

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Causal Inference in Statistics fills that gap. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality.

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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.