Iain Pardoe

Applied Regression Modeling


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      Applied Regression Modeling

       Third Edition

      Iain Pardoe Thompson Rivers University The Pennsylvania State University

Logo: Wiley

      This edition first published 2021

      © 2021 John Wiley & Sons, Inc

       Edition History

      Second Edition, 2012, John Wiley & Sons, Inc

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

      The right of Iain Pardoe to be identified as the author of this work has been asserted in accordance with law.

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      While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

       Library of Congress Cataloging‐in‐Publication Data

      Names: Pardoe, Iain, 1970- author

      Title: Applied regression modeling / Iain Pardoe, Thompson Rivers

      University, The Pennsylvania State University.

      Description: Third edition. | Hoboken, New Jersey : Wiley, [2020] |

      includes bibliographical references and index.

      Identifiers: LCCN 2020028117 (print) | LCCN 2020028118 (ebook) | ISBN

      9781119615866 (cloth) | ISBN 9781119615880 (adobe pdf) | ISBN

      9781119615903 (epub)

      Subjects: LCSH: Regression analysis. | Statistics.

      Classification: LCC QA278.2 .P363 2020 (print) | LCC QA278.2 (ebook) |

      DDC 519.5/36–dc23

      LC record available at https://lccn.loc.gov/2020028117

      LC ebook record available at https://lccn.loc.gov/2020028118

      Cover Design: Wiley

      Cover Image: Courtesy of Bethany Pardoe

      The first edition of this book was developed from class notes written for an applied regression course taken primarily by undergraduate business majors in their junior year at the University of Oregon. Since the regression methods and techniques covered in the book have broad application in many fields, not just business, the second edition widened its scope to reflect this. This third edition refines and improves the text further. Details of the major changes for the third edition are included at the end of this preface.

      The book is suitable for any undergraduate or graduate statistics course in which regression analysis is the main focus. A recommended prerequisite is an introductory probability and statistics course. It is also appropriate for use in an applied regression course for MBAs and for vocational, professional, or other non‐degree courses. Mathematical details have deliberately been kept to a minimum, and the book does not contain any calculus. Instead, emphasis is placed on applying regression analysis to data using statistical software, and understanding and interpreting results. Optional formulas are provided for those wishing to see these details and the book now includes an informal overview of matrices in the context of multiple linear regression.