This edition first published 2019
© 2019 John Wiley & Sons, Inc.
Edition History
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Library of Congress Cataloging‐in‐Publication Data
Names: Denis, Daniel J., 1974– author.
Title: SPSS data analysis for univariate, bivariate, and multivariate statistics / Daniel J. Denis.
Description: Hoboken, NJ : Wiley, 2019. | Includes bibliographical references and index. |
Identifiers: LCCN 2018025509 (print) | LCCN 2018029180 (ebook) | ISBN 9781119465805 (Adobe PDF) | ISBN 9781119465782 (ePub) | ISBN 9781119465812 (hardcover)
Subjects: LCSH: Analysis of variance–Data processing. | Multivariate analysis–Data processing. | Mathematical statistics–Data processing. | SPSS (Computer file)
Classification: LCC QA279 (ebook) | LCC QA279 .D45775 2019 (print) | DDC 519.5/3–dc23
LC record available at https://lccn.loc.gov/2018025509
Cover Design: Wiley
Cover Images: © GarryKillian/Shutterstock
The goals of this book are to present a very concise, easy‐to‐use introductory primer of a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences, and to get you started doing data analysis fast. The emphasis on the book is data analysis and drawing conclusions from empirical observations. The emphasis of the book is not on theory. Formulas are given where needed in many places, but the focus of the book is on concepts rather than on mathematical abstraction. We emphasize computational tools used in the discovery of empirical patterns and feature a variety of popular statistical analyses and data management tasks that you can immediately apply as needed to your own research. The book features analyses and demonstrations using SPSS. Most of the data sets analyzed are very small and convenient, so entering them into SPSS should be easy. If desired, however, one can also download them from www.datapsyc.com. Many of the data sets were also first used in a more theoretical text written by the same author (see Denis, 2016), which should be consulted for a more in‐depth treatment of the topics presented in this book. Additional references for readings are also given throughout the book.
This is a “how‐to” book and will be of use to undergraduate and graduate students along with researchers and professionals who require a quick go‐to source, to help them perform essential statistical analyses and data management tasks. The book only assumes minimal prior knowledge of statistics, providing you with the tools you need right now to help you understand and interpret your data analyses. A prior introductory course in statistics at the undergraduate level would be helpful, but is not required for this book. Instructors may choose to use the book either as a primary text for an undergraduate or graduate course or as a supplement to a more technical text, referring to this book primarily for the “how to’s” of data analysis in SPSS. The book can also be used for self‐study. It is suitable for use as a general reference in all social and natural science fields and may also be of interest to those in business who use SPSS for decision‐making. References to further reading are provided where appropriate should the reader wish to follow up on these topics or expand one’s knowledge base as it pertains to theory and further applications. An early chapter reviews essential statistical and research principles usually covered in an introductory statistics course, which should be sufficient for understanding the rest of the book and interpreting analyses. Mini brief sample write‐ups are also provided for select analyses in places to give the reader a starting point to writing up his/her own results for his/her thesis, dissertation, or publication. The book is meant to be an easy, user‐friendly introduction to a wealth of statistical methods while simultaneously demonstrating their implementation in SPSS. Please contact me at daniel.denis@umontana.edu or email@datapsyc.com with any comments or corrections.
When you see this symbol, it means a brief sample write‐up has been provided for the accompanying output. These brief write‐ups can be used as starting points to writing up your own results for your thesis/dissertation or even publication.
When you see this symbol, it means a special note, hint, or reminder has been provided or signifies extra insight into something not thoroughly discussed in the text.
When you see this symbol, it means a special WARNING has been issued that if not followed may result in a serious error.
Thanks go out to Wiley for publishing this book, especially to Jon Gurstelle for presenting the idea to Wiley and securing the contract for the book and to Mindy Okura‐Marszycki for taking over the project after Jon left. Thank you Kathleen Pagliaro for keeping in touch about this project and the former book. Thanks goes out to everyone (far too many to mention) who have influenced me in one way or another in my views and philosophy about statistics and science, including undergraduate and graduate students whom I have had the pleasure of teaching (and learning from) in my courses taught at the University of Montana.
This book is dedicated to all military veterans of the United States of America, past, present, and future, who teach us that all problems are relative.
