Introduction

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.

Features

- 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