William Dale Berry - Understanding regression assumptions

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title	:	Understanding Regression Assumptions Sage University Papers Series. Quantitative Applications in the Social Sciences ; No. 07-092
author	:	Berry, William Dale.
publisher	:	Sage Publications, Inc.
isbn10 | asin	:	080394263X
print isbn13	:	9780803942639
ebook isbn13	:	9780585217222
language	:	English
subject	Social sciences--Statistical methods, Regression analysis, Error analysis (Mathematics)
publication date	:	1993
lcc	:	HA31.3.B47 1993eb
ddc	:	300/.1/519536
subject	:	Social sciences--Statistical methods, Regression analysis, Error analysis (Mathematics)

Understanding Regression Assumptions

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 i Series/Number 07-092 Understanding Regression Assumptions William D. Berry Florida State University SAGE PUBLICATIONS International Educational and Professional Publisher Newbury Park London New Delhi

Page ii Copyright 1993 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: 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 Berry, William Dale. Understanding regression assumptions / William D. Berry. p. cm.(Quantitative applications in the social sciences; 92) Includes bibliographical references. ISBN 0-8039-4263-X (pbk.) 1. Social sciencesStatistical methods. 2. Regression analysis. 3. Error analysis (Mathematics) I. Title. II. Series: Sage university papers series. Quantitative applications in the social sciences; 92. HA31.3.B47 1993 300'.1'519536dc20 92-42925 98 99 00 01 10 9 8 7 6 5 Sage Production Editor: Diane S. Foster When citing a university paper, please use the proper form. Remember to cite the current 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) BERRY, W. D. (1993) Understanding Regression Assumptions. Sage University Paper series on Quantitative Applications in the Social Sciences, 07-092. Newbury Park, CA: Sage. OR (2) Berry, W. D. (1993) Understanding regression assumptions (Sage University Paper series on Quantitative Applications in the Social Sciences, series no. 07-092). Newbury Park, CA: Sage.

Page iii Contents Series Editor's Introduction v Acknowledgments vii 1. Introduction 1 2. A Formal Presentation of the Regression Assumptions 3 The Regression Surface 3 The Role of the Error Term 6 Other Regression Assumptions 11

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