Regression Analysis Theory, Methods and Applications
Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em pirically identifying how a variable i
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Springer Texts in Statistics Alfred
Elements of Statistics for the Life and Social Sciences
Biom
Probability and Statistics: Theory and Applications
Chow and Teicher
Probability Theory: Independence, Interchangeability, Martingales. Second Edition
Christensen
Plane Answers to Complex Questions: The Theory of Linear Models
du Toit, Steyn and Strumpf
Graphical Exploratory Data Analysis
Finkelstein and Levin
Statistics for Lawyers
Kalbfleisch
Probability and Statistical Inference: Volume 1: Probability. Second Edition
Kalbfleisch
Probability and Statistical Inference: Volume 2: Statistical Inference. Second Edition
Keyfitz
Applied Mathematical Demography. Second Edition
Kiefer
Introduction to Statistical Inference
Kokoska and Nevison
Statistical Tables and Fonnulae
Madansky
Prescriptions for Working Statisticians
McPherson
Statistics in Scientific Investigation: Basis, Application, and Interpretation
Nguyen and Rogers
Fundamentals of Mathematical Statistics: Volume I: Probability for Statistics
Nguyen and Rogers
Fundamentals of Mathematical Statistics: Volume 11: Statistical Inference
Peters
Counting for Something: Statistical Principles and Personalities (continued after index)
Ashish Sen
Muni Srivastava
Regression Analysis
Theory, Methods, and Applications
With 38 Illustrations
Springer Science+Business Media, LLC
Ashish Sen College of Architecture, Art, and Urban Planning School of Urban Planning and Policy The University of Illinois Chicago, IL 60680 USA Muni Srivastava Department of Statistics University of Toronto Toronto, Ontario Canada M5S lAI
Mathematical Subject Classification: 62Jxx, 62-01 Library of Congress Cataloging-in-Publication Data Sen, Ashish K. Regression analysis: Tbeory, methods, and applications/Ashish Sen, Muni Srivastava. p. cm.-(Springer texts in statistics)
ISBN 978-3-540-97211-2 DOI 10.1007/978-3-662-25092-1 l. Regression analysis. III. Series. QA278.2.S46 1990 519.5'36-dc20
ISBN 978-3-662-25092-1 (eBook)
I. Srivastava, M.S.
11. Title. 89-48506
Printed on acid-free paper. © 1990 Springer Scienee+Business Media New York
OriginaIly published by Springer-Verlag New York Ine. in 1990 Softcover reprint ofthe hardcover 1st edition 1990 All rights reserved. Tbis work may not be translated or copied in whole or in part without the wrilten permission of the publisher Springer Science+Business Media, LLC, except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. Tbe use of general descriptive names, Irade names, trademarks, etc., in this publication, even if the former are not especially identified, is not to be taken as a sign that such names, as understood by the Trade Marks and Merchandise Marks Act, may accordingly be used freely by anyone. Photocomposed copy prepared by authors using LaTeX. 987654321
ISBN 978-3-540-97211-2
To Ashoka Kumar
