# Introduction to Bayesian Statistics

Praise for the First Edition

"I cannot think of a better book for teachers of introductory statistics who want a readable and pedagogically sound text to introduce Bayesian statistics."
Statistics in Medical Research

"[This book] is written in a lucid conversational style, which is so rare in mathematical writings. It does an

## Overview

Praise for the First Edition

"I cannot think of a better book for teachers of introductory statistics who want a readable and pedagogically sound text to introduce Bayesian statistics."
Statistics in Medical Research

"[This book] is written in a lucid conversational style, which is so rare in mathematical writings. It does an excellent job of presenting Bayesian statistics as a perfectly reasonable approach to elementary problems in statistics."
STATS: The Magazine for Students of Statistics, American Statistical Association

"Bolstad offers clear explanations of every concept and method making the book accessible and valuable to undergraduate and graduate students alike."
Journal of Applied Statistics

The use of Bayesian methods in applied statistical analysis has become increasingly popular, yet most introductory statistics texts continue to only present the subject using frequentist methods. Introduction to Bayesian Statistics, Second Edition focuses on Bayesian methods that can be used for inference, and it also addresses how these methods compare favorably with frequentist alternatives. Teaching statistics from the Bayesian perspective allows for direct probability statements about parameters, and this approach is now more relevant than ever due to computer programs that allow practitioners to work on problems that contain many parameters.

This book uniquely covers the topics typically found in an introductory statistics book—but from a Bayesian perspective—giving readers an advantage as they enter fields where statistics is used. This Second Edition provides:

• Extended coverage of Poisson and Gamma distributions

• Two new chapters on Bayesian inference for Poisson observations and Bayesian inference for the standard deviation for normal observations

• A twenty-five percent increase in exercises with selected answers at the end of the book

• A calculus refresher appendix and a summary on the use of statistical tables

• New computer exercises that use R functions and Minitab® macros for Bayesian analysis and Monte Carlo simulations

Introduction to Bayesian Statistics, Second Edition is an invaluable textbook for advanced undergraduate and graduate-level statistics courses as well as a practical reference for statisticians who require a working knowledge of Bayesian statistics.

## Editorial Reviews

From the Publisher
"I would recommend this book if you are interested in teaching an introductory in Bayesian statistics…"  (The American Statistician, February 2006)

"…a very useful undergraduate text presenting a novel approach to an introductory statistics course." (Biometrics, September 2005)

"I cannot think of a better book for teachers of introductory statistics who want a readable and pedagogically sound text to introduce Bayesian statistics." (Statistics in Medical Research, October 2005)

"…this book fills a gap for teaching elementary Bayesian statistics…it could easily serve as a self-learning text…" (Technometrics, May 2005)

[In a review comparing Bolstad with another book,] "I will keep both of these books on my shelf, but I expect that Bolstad will be the one most borrowed by my colleagues."(significance, December 2004)

"...does an excellent job of presenting Bayesian Statistics as a perfectly reasonable approach to elementary problems of statistics…I must heartily recommend this book…" (STATS: The Magazine for Students of Statistics, Fall 2004)

## Product Details

ISBN-13:
9781118619216
Publisher:
Wiley
Publication date:
06/05/2013
Sold by:
Barnes & Noble
Format:
NOOK Book
Pages:
464
File size:
14 MB
Note:

## Related Subjects

From the Publisher
"The general tenor of this book is good and it should serve well as a text for an introductory statistics course taught from a Bayesian perspective." (Biometrics, September 2008)

"Like the first edition, this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods. (Technometrics, November 2008)

"Like the first edition, this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels.  It is a well-written book on elementary Bayesian inference, and the material is easily accessible.  It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." (Technometrics, November 2008)

## Meet the Author

William M. Bolstad, PhD, is Senior Lecturer in the Department of Statistics at The University of Waikato, New Zealand. He holds degrees from the University of Missouri, Stanford University, and The University of Waikato. Dr. Bolstad's research interests include Bayesian statistics, MCMC methods, recursive estimation techniques, multiprocess dynamic time series models, and forecasting.

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