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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.

Details e-book Causal Inference in Statistics - A Primer

🗸 Author(s):
🗸 Title: Causal Inference in Statistics - A Primer
🗸 Rating : 4.5 from 5 stars (191 reviews)
🗸 ISBN-10: 1119186846
🗸 ISBN-13: 9781119186847
🗸 Languange: English
🗸 Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
🗸 Supported Devices: Android, iOS, PC and Amazon Kindle

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