A Student’s Guide to Bayesian Statistics

Nonfiction, Social & Cultural Studies, Social Science, Methodology, Reference & Language, Reference, Research
Cover of the book A Student’s Guide to Bayesian Statistics by Ben Lambert, SAGE Publications
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Author: Ben Lambert ISBN: 9781526418265
Publisher: SAGE Publications Publication: April 20, 2018
Imprint: SAGE Publications Ltd Language: English
Author: Ben Lambert
ISBN: 9781526418265
Publisher: SAGE Publications
Publication: April 20, 2018
Imprint: SAGE Publications Ltd
Language: English

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics.

Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers:

  • An introduction to probability and Bayesian inference
  • Understanding Bayes' rule 
  • Nuts and bolts of Bayesian analytic methods
  • Computational Bayes and real-world Bayesian analysis
  • Regression analysis and hierarchical methods

This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics.

Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers:

This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses.

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