ABSTRACT

A Balanced Treatment of Bayesian and Frequentist Inference- Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on both perspectives than the first edition.
New to the Second Edition:

New material on empirical Bayes and penalized likelihoods and their impact on regression models
Expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models
More examples and exercises
More comparison between the approaches, including their similarities and differences

Designed for advanced undergraduate and graduate courses, the text thoroughly covers statistical inference without delving too deep into technical details. It compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two. Many examples illustrate the methods and models, and exercises are included at the end of each chapter.

chapter 1|20 pages

Introduction

chapter 2|44 pages

Elements of inference

chapter 3|34 pages

Prior distribution

chapter 4|64 pages

Estimation

chapter 5|58 pages

Approximating methods

chapter 6|42 pages

Hypothesis testing

chapter 7|18 pages

Prediction

chapter 8|38 pages

Introduction to linear models