An introductory handbook of Bayesian thinking /

As Bayesian techniques become more common across a variety of fields, it becomes important for experts in those fields to understand those methods. An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for...

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Bibliographic Details
Main Author: Loftus, Stephen C. (Author)
Corporate Author: ScienceDirect (Online service)
Format: eBook
Language:English
Published: [London] : Academic Press, [2025]
Subjects:
Online Access:Connect to the full text of this electronic book

MARC

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520 |a As Bayesian techniques become more common across a variety of fields, it becomes important for experts in those fields to understand those methods. An Introductory Handbook of Bayesian Thinking brings Bayesian thinking and methods to a wide audience beyond the mathematical sciences. Appropriate for students with some background in calculus and introductory statistics, particularly for nonstatisticians with a sufficient mathematical background, the text provides a gentle introduction to Bayesian ideas with a wide array of supporting examples from a variety of fields. Utilizes real datasets to illustrate Bayesian models and their results Guides readers on coding Bayesian models using the statistical software R, including a helpful introduction and supporting online resource Appropriate for an undergraduate statistics course, as well as for non-statisticians with sufficient mathematical background (integral and differential Calculus and an introductory Statistics course) Covers any more advanced topics which readers may not be familiar with--such as the basic idea of vectors and matrices--as much as needed in order to foster understanding of core concepts. 
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