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Gudmund R. Iversen - Bayesian statistical inference

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Empirical researchers, for whom Iversens volume provides an introduction, have generally lacked a grounding in the methodology of Bayesian inference. As a result, applications are few. After outlining the limitations of classical statistical inference, the author proceeds through a simple example to explain Bayes theorem and how it may overcome these limitations. Typical Bayesian applications are shown, together with the strengths and weaknesses of the Bayesian approach. This monograph thus serves as a companion volume for Henkels Tests of Significance (QASS vol 4).

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title Bayesian Statistical Inference Sage University Papers Series - photo 1

title:Bayesian Statistical Inference Sage University Papers Series. Quantitative Applications in the Social Sciences ; No. 07-043
author:Iversen, Gudmund R.
publisher:Sage Publications, Inc.
isbn10 | asin:0803923287
print isbn13:9780803923287
ebook isbn13:9780585180861
language:English
subjectBayesian statistical decision theory.
publication date:1984
lcc:QA279.5.I94 1984eb
ddc:519.5/42
subject:Bayesian statistical decision theory.
Bayesian Statistical Inference
SAGE UNIVERSITY PAPERS
Series: Quantitative Applications in the Social Sciences
Series Editor: Michael S. Lewis-Beck, University of Iowa
Editorial Consultants
Richard A. Berk, Sociology, University of California, Los Angeles
William D. Berry, Political Science, Florida State University
Kenneth A. Bollen, Sociology, University of North Carolina, Chapel Hill
Linda B. Bourque, Public Health, University of California, Los Angeles
Jacques A. Hagenaars, Social Sciences, Tilburg University
Sally Jackson, Communications, University of Arizona
Richard M. Jaeger, Education, University of North Carolina, Greensboro
Gary King, Department of Government, Harvard University
Roger E. Kirk, Psychology, Baylor University
Helena Chmura Kraemer, Psychiatry and Behavioral Sciences, Stanford University
Peter Marsden, Sociology, Harvard University
Helmut Norpoth, Political Science, SUNY, Stony Brook
Frank L. Schmidt, Management and Organization, University of Iowa
Herbert Weisberg, Political Science, The Ohio State University
Publisher
Sara Miller McCune, Sage Publications, Inc.
INSTRUCTIONS TO POTENTIAL CONTRIBUTORS
For guidelines on submission of a monograph proposal to this series, please write
Michael S. Lewis-Beck, Editor
Sage QASS Series
Department of Political Science
University of Iowa
Iowa City, IA 52242
Page 1
Series / Number 07-043
Bayesian Statistical Inference
Gudmund R. Iversen
Swarthmore College
Picture 2
SAGE PUBLICATIONS
The International Professional Publishers
Newbury Park London New Delhi
Page 2
Copyright 1984 by Sage Publications, Inc.
All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.
For information address:
Picture 3
SAGE Publications, Inc.
2455 Teller Road
Newbury Park, California 91320
E-mail: order@sagepub.com
SAGE Publications Ltd.
6 Bonhill Street
London EC2A 4PU
United Kingdom
SAGE Publications India Pvt. Ltd.
M-32 Market
Greater Kailash I
New Delhi 110 048 India
Printed in the United States of America
International Standard Book Number 0-8039-2328-7
Library of Congress Catalog Card No. 84-050890
98 99 00 01 15 14 13 12 11 10
When citing a University Paper, please use the proper form. Remember to cite the correct Sage University Paper series title and include the paper number. One of the following formats can be adapted (depending on the style manual used):
(1) Iversen, G. R., & Norpoth, H. (1976). Analysis of variance (Sage University Paper series on Quantitative Applications in the Social Sciences, No. 07-001). Beverly Hills, CA: Sage.
OR
(2) Iversen, G. R., & Norpoth, H. 1976. Analysis of variance. Sage University Paper series on Quantitative Applications in the Social Sciences, series no. 07-001. Beverly Hills, CA: Sage.
Page 3
Contents
Series Editor's Introduction
5
1. Thomas Bayes and Statistical Inference
7
2. Classical Statistical Inference
9
Picture 4
Use of Tail Probabilities
10
Picture 5
Interpretation of Confidence Intervals
11
Picture 6
Uncertainty about Parameter Values
11
3. Bayes' Theorem
12
Picture 7
Derivation
12
Picture 8
An Example
13
Picture 9
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