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John K. Kruschke - Doing Bayesian Data Analysis: A Tutorial with R and BUGS

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Book:
Doing Bayesian Data Analysis: A Tutorial with R and BUGS
Author:
John K Kruschke
Publisher:
Academic Press
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Books / Romance novel
Year:
2010
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There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of all scenarios addressed by non-Bayesian textbooks--t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). This book is intended for first year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Prerequisite is knowledge of algebra and basic calculus. Free software now includes programs in JAGS, which runs on Macintosh, Linux, and Windows. - Accessible, including the basics of essential concepts of probability and random sampling - Examples with R programming language and BUGS software - Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) - Coverage of experiment planning - R and BUGS computer programming code on website - Exercises have explicit purposes and guidelines for accomplishment.

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Front Matter

Doing Bayesian Data Analysis

Doing Bayesian Data Analysis

A Tutorial with R and BUGS

John K. Kruschke

Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN

AMSTERDAM BOSTON HEIDELBERG LONDON OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Doing Bayesian Data Analysis A Tutorial with R and BUGS - image 2

Academic Press is an imprint of Elsevier

30 Corporate Drive, Suite 400, Burlington, MA 01803, USA

Elsevier, The Boulevard, Langford Lane, Kidlington, Oxford, OX5 1GB, UK

No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher's permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions.

This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.

Library of Congress Cataloging-in-Publication Data

Application submitted

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library.

ISBN: 978-0-12-381485-2

For information on all Academic Press publications visit our Web site at www.elsevierdirect.com

Printed in the United States of America

10 11 12 13 9 8 7 6 5 4 3 2 1

Dedication

Dedicated to my mother, Marilyn A. Kruschke,

and to the memory of my father, Earl R. Kruschke,

who both brilliantly exemplified and taught sound reasoning.

And, in honor of my father,

who dedicated his first book to his children,

I also dedicate this book to mine:

Claire A. Kruschke and Loren D. Kruschke

Chapter 1. This Book's Organization

Read Me First!

Contents

1.1

1.2

1.3

1.3.1

1.3.2

1.4

1.5

Oh honey I'm searching for love that is true,

But driving through fog is so dang hard to do.

Please paint me a line on the road to your heart,

I'll rev up my pick up and get a clean start.

1.1. Real People can Read This Book

This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours). The book starts at the basics, with notions of probability and programming, then progresses to advanced hierarchical models that are used in realistic data analysis. In other words, you do not need to already know statistics and programming. This book is speaking to a first-year graduate student or advanced undergraduate in the social or biological sciences: someone who grew up in Lake Wobegon, mythical being who has the previous training of a nuclear physicist and then decided to learn about Bayesian statistics.

1A popular weekly radio show on National Public Radio, called A Prairie Home Companion, features fictional anecdotes about a small town named Lake Wobegon. The stories, written and orated by Garrison Keillor, always end with the phrase, And that's the news from Lake Wobegon, where all the women are strong, all the men are good looking, and all the children are above average. So, if you grew up there, .

This book provides broad coverage and ease of access. describes the contents in a bit more detail, but here are some highlights. This book covers Bayesian analogues of all the traditional statistical tests that are presented in introductory statistics textbooks, including

-tests, analysis of variance (ANOVA), regression, chi-square tests, and so on. This book also covers crucial issues for designing research, such as statistical power and methods for determining the sample size needed to achieve a desired research goal. And you don't need to already know statistics to read this book, which starts at the beginning, including introductory chapters about concepts of probability and an entire chapter devoted to Bayes' rule. The important concept of hierarchical modeling is introduced with unique simple examples, and the crucial methods of Markov chain Monte Carlo sampling are explained at length, starting with simple examples that, again, are unique to this book. Computer programs are thoroughly explained throughout the book and are listed in their entirety, so you can use and adapt them to your own needs.

But wait, there's more. As you may have noticed from the beginning of this chapter, the chapters commence with a stanza of elegant and insightful verse composed by a famous poet. The quatrains or, colloquially speaking, country waltz meter. The poems regard conceptual themes of the chapter via allusion from immortal human motifs often expressed by country western song lyrics, all in waltz timing.

2quatrain [noun]: Four lines of verse. (Unless it's written qua train, in which case it's a philosopher comparing something to a locomotive.)

3dactylic [adj.]: A metrical foot in poetry comprising one stressed and two unstressed syllables. (Not to be confused with a pterodactyl, which was a flying dinosaur and which probably sounded nothing like a dactyl unless it fell from the sky and bounced twice: THUMP-bump-bump.)

4tetrameter [noun]: A line of verse containing four metrical feet. (Not to be confused with a quadraped, which has four feet but is averse to lines.)

If you do not find them to be all that funny,

if they leave you wanting back all of your money,

well honey some waltzing's a small price to pay,

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