SPSS Statistics for Data Analysis and Visualization

511 Pages·2017·31.38 MB·English

by  Keith McCormick

SPSS® Statistics
for Data Analysis
and Visualization
SPSS® Statistics
for Data Analysis
and Visualization
Keith McCormick
Jesus Salcedo
with
Jon Peck and Andrew Wheeler
SPSS® Statistics for Data Analysis and Visualization
Published by
John Wiley & Sons, Inc.
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Copyright © 2017 by John Wiley & Sons, Inc., Indianapolis, Indiana
Published simultaneously in Canada
ISBN: 978-1-119-00355-7
ISBN: 978-1-119-00557-5 (ebk)
ISBN: 978-1-119-00366-3 (ebk)
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We would like to dedicate this book to Jon Peck, who retired from
more than 30 years with SPSS and IBM while this book was
in its final stages. We wish him the best of retirements even
though he probably won’t be able to resist staying in the
SPSS community in some form.
About the Authors
Keith McCormick is a data mining consultant, trainer, and speaker. A passionate
user of SPSS for 25 years, he has trained thousands on how to effectively use
SPSS Statistics and SPSS Modeler. He blogs at keithmccormick.com.
Jesus Salcedo is an independent statistical consultant. He is a former SPSS
Curriculum Team Lead and Senior Education Specialist, who has written numer-
ous SPSS training courses and trained thousands of users.
Jon Peck, recently retired from IBM and SPSS, was instrumental in developing
and introducing the R and Python connections to the SPSS community. This
expertise made him uniquely qualified to produce Chapter 18. He is the author
of all the extension commands discussed in that chapter and has a patent pend-
ing on the algorithm in SPSSINC TURF procedure discussed there. He can be
reached at [email protected].
Andrew Wheeler is a professor of criminology at the University of Texas at
Dallas and a former crime analyst. The application of geospatial techniques
in his research created the opportunity for a powerful real world example in
Chapter 8. He has used SPSS for over 10 years, and often blogs SPSS tutorials
at andrewpwheeler.wordpress.com.
vii
About the Technical Editors
Jon Peck, now retired from IBM, was a senior engineer, statistician, and
product strategy person for SPSS and IBM for 32 years. He earned a Ph.D in
economics from Yale University, and taught econometrics and statistics there
for 13 years before joining SPSS. He designed and contributed to many features
of SPSS Statistics and has consulted with and trained many users. He remains
active on social media and in consulting.
Terry Taerum has fifteen years’ experience as a statistician at the University of
Alberta, fifteen years as a data analyst at SPSS Inc., and five years as a predictive
analyst and consultant with IBM Inc.
ix
Credits
Project Editor Business Manager
Tom Dinse Amy Knies
Technical Editors Executive Editor
Jon Peck Jim Minatel
Terry Taerum
Project Coordinator, Cover
Production Editor Brent Savage
Dassi Zeidel
Proofreader
Copy Editor Nancy Carrasco
Kim Cofer
Indexer
Production Manager Johnna VanHoose Dinse
Katie Wisor
Cover Designer
Manager of Content Development Wiley
& Assembly
Cover Image
Mary Beth Wakefield
iStock.com/agsandrew
Marketing Manager
Christie Hilbrich
Professional Technology &
Strategy Director
Barry Pruett
xi
Acknowledgments
Keith and Jesus are especially proud to have worked with Bob Elliot before he
retired. Our good friend Dean Abbott recommended Keith to Bob when Bob
was seeking out a follow up to Dean’s excellent Applied Predictive Analytics,
but specifically in SPSS Statistics. Without both of them, this book would not
have been created.
Terry’s and Jon’s contribution extended well beyond technical reviewing. We
consider both of them mentors and friends. Jon took over technical reviewing
when Terry took on a new role with a return to IBM. Jon, in particular, was an
interlocutor and trusted advisor, and we produced a better book as a result.
Tom, our project editor, had to be patient with us. Deadlines slipped, con-
tributors became unavailable, and Bob retired before the book was complete.
Whenever it seemed that something wasn’t quite as it should be, it was often
Tom that ultimately made it right. He deserves credit for multiple roles, and
we thank him.
We would also like to thank all of the many SPSSers that we turn to when
we have a question even if they haven’t heard from us in a while. We love the
sense of community that we have all managed to maintain even when so many
have moved on to other roles. And we thank Jason for capturing that sense of
community in his foreword.
xiii
Contents at a Glance
Foreword xxiii
Introduction xxvii
Part I Advanced Statistics 1
Chapter 1 Comparing and Contrasting IBM SPSS AMOS with Other
Multivariate Techniques 3
Chapter 2 Monte Carlo Simulation and IBM SPSS Bootstrapping 43
Chapter 3 Regression with Categorical Outcome Variables  71
Chapter 4 Building Hierarchical Linear Models 101
Part II Data Visualization 129
Chapter 5 Take Your Data Visualizations to the Next Level  131
Chapter 6 The Code Behind SPSS Graphics:
Graphics Production Language  147
Chapter 7 Mapping in IBM SPSS Statistics  173
Chapter 8 Geospatial Analytics  193
Chapter 9 Perceptual Mapping with Correspondence Analysis,
GPL, and OMS 217
Chapter 10 Display Complex Relationships with
Multidimensional Scaling  249
Part III Predictive Analytics 271
Chapter 11 SPSS Statistics versus SPSS Modeler:
Can I Be a Data Miner Using SPSS Statistics?  275
Chapter 12 IBM SPSS Data Preparation  303
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xvi Contents at a Glance
Chapter 13 Model Complex Interactions with IBM SPSS
Neural Networks 325
Chapter 14 Powerful and Intuitive: IBM SPSS Decision Trees 355
Chapter 15 Find Patterns and Make Predictions with K Nearest
Neighbors 379
Part IV Syntax, Data Management, and Programmability 393
Chapter 16 Write More Efficient and Elegant Code with
SPSS Syntax Techniques 395
Chapter 17 Automate Your Analyses with SPSS Syntax and the Output
Management System  421
Chapter 18 Statistical Extension Commands  441
Index 473