A student's guide to Bayesian statistics
Lambert, Ben
A student's guide to Bayesian statistics created by Ben Lambert - London Sage 2018 - 498 pages ill. 25 cm
Includes bibliographical references and index
An introduction to Bayesian inference -- Understanding the Bayesian formula -- Analytic Bayesian methods -- A practical guide to doing real-life Bayesian analysis: Computational Bayes -- Hierarchical models and regression.
"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." --
9781473916364 1473916364 9781473916357 1473916356
Bayesian statistical decision theory
Bayesian statistical decision theory
QA279.5
A student's guide to Bayesian statistics created by Ben Lambert - London Sage 2018 - 498 pages ill. 25 cm
Includes bibliographical references and index
An introduction to Bayesian inference -- Understanding the Bayesian formula -- Analytic Bayesian methods -- A practical guide to doing real-life Bayesian analysis: Computational Bayes -- Hierarchical models and regression.
"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." --
9781473916364 1473916364 9781473916357 1473916356
Bayesian statistical decision theory
Bayesian statistical decision theory
QA279.5