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Icon Function
Icon Function
Icon
Function
Click this to open a file
Save current file
Print file
Recall a recently-
used command
Undo the last operation
Redo something you
just undid
Find data
Insert subject or case
into the data file
Insert new variable
into the data file
Split file into subgroups
Weight cases
Select cases
(upper left corner) the “+” sign
indicates that this is the active file
Go to a particular variable
or case number
Access information about
the current variable
Shifts between numbers and labels
for variables with several levels
Use subsets of variables/use
all variables
Spell check
Front 2
Open Data
Screen
Folder or disk
drive to look in
Move up to the
next highest folder
or disk drive
Files in the folder
Click when all
boxes have correct
information
Type file name
Identify the file type
In case you change
your mind
Front 1
Initial data
screen
Menu commands
Variables
Toolbar icons
Subject or case
numbers
Empty data cells
Scroll bars
“Data View” and
“Variable View” tabs
Minimize and
maximize buttons
Page 2
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IBM SPSS Statistics
26 Step by Step
IBM SPSS Statistics 26 Step by Step: A Simple Guide and Reference, sixteenth edition, takes a straight-
forward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers
alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through
the program. Output for each procedure is explained and illustrated, and every output term is defined.
Exercises at the end of each chapter support students by providing additional opportunities to practice
using SPSS.
This book covers the basics of statistical analysis and addresses more advanced topics such as multi-
dimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA
(between- and within-subjects), cluster analysis, Log-linear models, logistic regression and a chapter
describing residuals. Back matter includes a description of data files used in exercises, an exhaustive glos-
sary, suggestions for further reading and a comprehensive index.
IBM SPSS Statistics 26 Step by Step is distributed in 85 countries, has been an academic best seller through
most of the earlier editions, and has proved invaluable aid to thousands of researchers and students.
New to this edition:
• Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 26
• How to handle missing data has been revised and expanded and now includes a detailed explanation
of how to create regression equations to replace missing data
• More explicit coverage of how to report APA style statistics; this primarily shows up in the Output
sections of Chapters 6 through 16, though changes have been made throughout the text.
Darren George is a Professor of Psychology at Burman University whose research focuses on intimate
relationships and optimal performance. He teaches classes in research methodology, statistics, personal-
ity/social psychology, and sport and performance psychology.
Paul Mallery is a Professor of Psychology at La Sierra University whose research focuses on the inter-
section of religion and prejudice. He teaches classes is research methodology, statistics, social psychology,
and political psychology.
Page 4
Page 5
IBM SPSS Statistics 26
Step by Step
A Simple Guide and Reference
sixteenth edition
Darren George
Burman University
Paul Mallery
La Sierra University
Page 6
Sixteenth edition published 2020
by Routledge
711 Third Avenue, New York, NY 10017
and by Routledge
2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
Routledge is an imprint of the Taylor & Francis Group, an informa business
� 2020 Taylor & Francis
The right of Darren George and Paul Mallery to be identified as authors of this work has
been asserted by them in accordance with sections 77 and 78 of the Copyright, Designs and
Patents Act 1988.
All rights reserved. No part of this book may be reprinted or reproduced or utilised in any
form or by any electronic, mechanical, or other means, now known or hereafter invented,
including photocopying and recording, or in any information storage or retrieval system,
without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks or registered trade-
marks, and are used only for identification and explanation without intent to infringe.
Thirteenth edition published by Pearson 2014
Fifteenth edition published by Routledge 2019
Library of Congress Cataloging in Publication Data
A catalog record has been requested for this book
ISBN: 978-1-138-49104-5 (hbk)
ISBN: 978-1-138-49107-6 (pbk)
ISBN: 978-1-351-03390-9 (ebk)
Publisher’s Note
This book has been prepared from camera-ready copy provided by the authors.
Visit the companion website: www.routledge.com/cw/george
Page 7
To Elizabeth
—D.G.
To my son Aydin, for his love of the arts and ways to improve the world
—P.M.
Page 8
Page 9
ix
Preface
xii
1 An Overview of IBM� SPSS�
Statistics
1
Introduction: An Overview of IBM SPSS Statistics 26
and Subscription Classic
1
1.1 Necessary Skills
1
1.2 Scope of Coverage
2
1.3 Overview
3
1.4 This Book’s Organization, Chapter by Chapter
3
1.5 An Introduction to the Example
4
1.6 Typographical and Formatting Conventions
5
2A IBM SPSS Statistics Processes for PC 8
2.1 The Mouse
8
2.2 The Taskbar and Start Menu
8
2.3 Common Buttons
10
2.4 The Data and Other Commonly
Used Windows
10
2.5 The Open Data File Dialog Window
13
2.6 The Output Window
16
2.7 Modifying or Rearranging Tables
19
2.8 Printing or Exporting Output
22
2.9 The “Options . . . ” Option: Changing the Formats 24
2B IBM SPSS Statistics Processes
for Mac
26
2.1 Selecting
26
2.2 The Desktop, Dock, and
Application Folder
27
2.3 Common Buttons
27
2.4 The Data and Other Commonly Used Windows
28
2.5 The Open Data File Dialog Window
30
2.6 The Output Window
34
2.7 Modifying or Rearranging Tables
36
2.8 Printing or Exporting Output
39
2.9 The “Options . . . ” Option: Changing the Formats 41
3 Creating and Editing a Data File
43
3.1 Research Concerns and Structure of the Data File 43
3.2 Step by Step
44
3.3 Entering Data
51
3.4 Editing Data
52
3.5 Grades.sav: The Sample Data File
54
Exercises
58
4 Managing Data
59
4.1 Step By Step: Manipulation of Data
60
4.2 The Case Summaries Procedure
60
4.3 Replacing Missing Values Procedure
63
4.4 The Compute Procedure: Creating New Variables 66
4.5 Recoding Variables
69
4.6 The Select Cases Option
73
4.7 The Sort Cases Procedure
75
4.8 Merging Files Adding Blocks of Variables or Cases 77
4.9 Printing Results
81
Exercises
82
5 Graphs and Charts: Creating and
Editing
83
5.1 Comparison of the Two Graphs Options
83
5.2 Types of Graphs Described
83
5.3 The Sample Graph
84
5.4 Producing Graphs and Charts
85
5.5 Bugs
87
5.6 Specific Graphs Summarized
88
5.7 Printing Results
99
Exercises
100
6 Frequencies
101
6.1 Frequencies
101
6.2 Bar Charts
101
6.3 Histograms
101
6.4 Percentiles
102
6.5 Step by Step
102
6.6 Printing Results
108
6.7 Output
108
Exercises
111
7 Descriptive Statistics
112
7.1 Statistical Significance
112
7.2 The Normal Distribution
113
7.3 Measures of Central Tendency
114
7.4 Measures of Variability Around the Mean
114
7.5 Measures of Deviation from Normality
114
7.6 Measures of Size of the Distribution
115
7.7 Measures of Stability: Standard Error
115
7.8 Step by Step
115
7.9 Printing Results
119
7.10 Output
119
Exercises
120
8 Crosstabulation and
χ2 Analyses
121
8.1 Crosstabulation
121
8.2 Chi-Square (χ2) Tests of Independence
121
8.3 Step by Step
123
8.4 Weight Cases Procedure: Simplified Data Setup 127
8.5 Printing Results
129
8.6 Output
129
Exercises
131
Contents
Page 10
x Contents
9 The Means Procedure
132
9.1 Step by Step
132
9.2 Printing Results
136
9.3 Output
136
Exercises
138
10 Bivariate Correlation
139
10.1 What is a Correlation?
139
10.2 Additional Considerations
141
10.3 Step by Step
142
10.4 Printing Results
146
10.5 Output
147
Exercises
148
11 The t Test Procedure
149
11.1 Independent-Samples t Tests
149
11.2 Paired-Samples t Tests
149
11.3 One-Sample t Tests
150
11.4 Significance and Effect Size
150
11.5 Step by Step
151
11.6 Printing Results
155
11.7 Output
155
Exercises
158
12 The One-Way ANOVA
Procedure
159
12.1 Introduction to One-Way Analysis of Variance
159
12.2 Step by Step
160
12.3 Printing Results
165
12.4 Output
165
Exercises
168
13 General Linear Model:
Two-Way ANOVA
169
13.1 Statistical Power
169
13.2 Two-Way Analysis of Variance
170
13.3 Step by Step
171
13.4 Printing Results
174
13.5 Output
174
Exercises
176
14 General Linear Model:
Three-Way ANOVA
177
14.1 Three-Way Analysis of Variance
177
14.2 The Influence of Covariates
178
14.3 Step by Step
179
14.4 Printing Results
181
14.5 Output
181
14.6 A Three-Way ANOVA that Includes a Covariate 186
Exercises
190
15 Simple Linear Regression
193
15.1 Predicted Values and the
Regression Equation
193
15.2 Simple Regression and the Amount of Variance
Explained
195
15.3 Testing for a Curvilinear Relationship
195
15.4 Step by Step
198
15.5 Printing Results
202
15.6 Output
203
15.7 A Regression Analysis that Tests for a Curvilinear
Trend
204
Exercises
205
16 Multiple Regression
Analysis
208
16.1 The Regression Equation
208
16.2 Regression and R2: The Amount of Variance
Explained
210
16.3 Curvilinear Trends, Model
Building, and References
210
16.4 Step by Step
212
16.5 Printing Results
217
16.6 Output
217
16.7 Change of Values as Each new
Variable is Added
218
Exercises
221
17 Nonparametric
Procedures
222
17.1 Step by Step
223
17.2 Are Observed Values Distributed
Differently than a Hypothesized Distribution?
225
17.3 Is the Order of Observed Values Non-Random? 227
17.4 Is a Continuous Variable Different in Different
Groups?
228
17.5 Are the Medians of a Variable
Different for Different Groups?
230
17.6 Are My Within-Subjects (Dependent
Samples or Repeated Measures) Measurements
Different?
231
17.7 Printing Results
234
18 Reliability Analysis
235
18.1 Coefficient Alpha (α)
236
18.2 Split-Half Reliability
236
18.3 The Example
236
18.4 Step by Step
237
18.5 Printing Results
241
18.6 Output
241
Exercises
246
Page 11
Contents xi
19 Multidimensional Scaling
247
19.1 Square Asymmetrical Matrixes
(The Sociogram Example)
248
19.2 Step by Step
249
19.3 Printing Results
255
19.4 Output
255
20 Factor Analysis
258
20.1 Create a Correlation Matrix
258
20.2 Factor Extraction
258
20.3 Factor Selection and Rotation
259
20.4 Interpretation
261
20.5 Step by Step
262
20.6 Output
268
21 Cluster Analysis
271
21.1 Cluster Analysis and Factor
Analysis Contrasted
271
21.2 Procedures for Conducting Cluster Analysis
272
21.3 Step by Step
274
21.4 Printing Results
280
21.5 Output
280
22 Discriminant Analysis
285
22.1 The Example: Admission into a Graduate
Program
286
22.2 The Steps Used in Discriminant Analysis
286
22.3 Step by Step
288
22.4 Output
293
23 General Linear Models:
MANOVA and MANCOVA
300
23.1 Step by Step
301
23.2 Printing Results
308
23.3 Output
309
Exercises
314
24 G.L.M.: Repeated-Measures
MANOVA
315
24.1 Step by Step
316
24.2 Printing Results
321
24.3 Output
321
Exercises
325
25 Logistic Regression
326
25.1 Step by Step
327
25.2 Printing Results
331
25.3 Output
332
26 Hierarchical Log-Linear
Models
336
26.1 Log-Linear Models
336
26.2 The Model Selection Log-Linear Procedure
337
26.3 Step by Step
338
26.4 Printing Results
342
26.5 Output
342
27 Nonhierarchical Log-Linear
Models
348
27.1 Models
348
27.2 A Few Words about Model Selection
349
27.3 Types of Models Beyond the Scope
of This Chapter
349
27.4 Step by Step
350
27.5 Printing Results
354
27.6 Output
354
28 Residuals: Analyzing
Left-Over Variance
357
28.1 Residuals
357
28.2 Linear Regression: A Case Study
358
28.3 General Log-Linear Models:
A Case Study
360
28.4 Accessing Residuals in SPSS
364
Data Files
367
Glossary
371
References
377
Credits
379
Index
381
Page 12
xii
Preface
IBM SPSS Statistics Software (“SPSS”) is a powerful tool that is capable of conduct-
ing just about any type of data analysis used in the social sciences, the natural sci-
ences, or in the business world. Mathematics is the language of science, and data
analysis is the dialect of research. The present book is designed to make data analysis
more comprehensible and less toxic.
In our teaching, we have frequently encountered students so traumatized by the
professor who cheerily says, “Analyze these data on SPSS; read the help files if you
need help” that they dropped the course rather than continue the struggle. It is in
response to this anguish that the present book was conceived. In our previous jobs
(before we became academic psychologists), Darren George taught high school mathe-
matics, and Paul Mallery programmed computers and trained people how to use them.
Both of us find great pleasure in the challenge of making a process that is intrinsically
complex as clear as possible. The ultimate goal in all our efforts with the present book
has been to make SPSS procedures, above all else, clear.
As the book started to take shape, a second goal began to emerge. In addition to
making SPSS procedures clear to the beginner, we wanted to create a tool that was an
effective reference for anyone conducting data analysis. This involved the expansion of
the original concept to include most of the major statistical procedures in SPSS Stan-
dard. The result of years of effort you now hold in your hands.
Although this edition is not a major update to the text, it does include many new
screenshots, output details that have changed, and improvemens to clarity through-
out. In addition, more significant improvements include:
• How to handle missing data has been significantly clarified in Chapter 4, with
additional information in Chapter 16 as well.
• Although we have always used APA style, this edition is more explicit in how
to report APA style statistics; this primarily shows up in the Output sections of
Chapters 6 through 16, though changes have been made throughout the text.
As usual, every step-by-step sequence has been executed and all outputs scruti-
nized to make certain everything in the current edition is accurate.
If you have been following the work of SPSS over the couple of years, you may have
heard of the “new interface” that is currently available (while still under development)
for the subscription version of SPSS. It is likely that this will become the primary ver-
sion of SPSS with SPSS 27. This will involve only minor changes to interpreting output
or the introductions to each chapter, but major changes to what you see and what you
click when you are following the step-by-step procedures. As the biggest revision of
SPSS since SPSS 16, the next version of SPSS will be a major departure (and a major
new edition of this book).
While the first 16 chapters of the book cover basic topics and would be under-
standable to many with very limited statistical background, the final 12 chapters
involve procedures that progressively require a more secure statistical grounding.
Those 12 chapters have provided our greatest challenge. At the beginning of each
chapter we spend several pages describing the procedure that follows. But, how can
one adequately describe, for instance, factor analysis or discriminant analysis in five
or six pages? The answer is simple: We can’t, but we can describe the procedures at a
common sense, conceptual level that avoids excessive detail and excessive emphasis
on computation that is useful as an introduction for beginners or as a useful adjunct to
more advanced reading or mentoring for more advanced data analysts. Writing these
introductions has not at all been simple. The chapter introductions are the most pains-
Page 13
takingly worked sections of the entire book. Although we acknowledge the absence
of much detail in our explanation of most procedures, we feel that we have done an
adequate job at a project that few would even attempt. How successful have we been at
achieving clarity in limited space? The fact that this book is now in its 16th edition, has
been an academic best seller for most of those editions, and is distributed in 85 coun-
tries of the world suggests that our efforts have not been in vain.
Authors’ Biographical Sketches and Present Addresses
Darren George is currently a professor of Psychology at:
Burman University
7630 University Drive
Lacombe, AB, T4L 2E5
403-782-3381, Ext. 4082
dgeorge@burmanu.ca
where he teaches personality psychology, social psychology, and research methods.
He completed his MA in Experimental Psychology (1982) at California State Univer-
sity, Fullerton; taught high school mathematics for nine years (1980–1989) at Mark
Keppel High School (Alhambra, CA) and Mountain View High School (El Monte, CA);
and then completed a Psychology PhD at UCLA (1992) with emphases in personality
psychology, social psychology, and measurement and psychometrics. Darren has now
been a professor at Burman University for 26 years.
Paul Mallery is currently a professor of Psychology at
La Sierra University
4500 Riverwalk Parkway
Riverside, CA, 92515
951-785-2528
pmallery@lasierra.edu
where he teaches social psychology and related courses and experimental method-
ology (including the application of SPSS). He received his PhD in Social Psychology
from UCLA (1994), with emphases in statistics and political psychology. He has been
on the faculty for 26 years, and still enjoys the challenge of teaching students to think
clearly about research using statistics.
Acknowledgments
As we look over the creative efforts of the past years, we wish to acknowledge several
people who have reviewed our work and offered invaluable insight and suggestions for
improvement. Our gratitude is extended to Richard Froman of John Brown University,
Michael A. Britt of Marist College, Marc L. Carter of the University of South Florida,
Randolph A. Smith of Ouachita Baptist University, Roberto R. Heredia of Texas A&M
International University, and several anonymous reviewers. We have had many editors
over the years, but are especially appreciative of Hannah Shakespeare for her excellent
guidance and commitment in the current edition. Further, we would like to express
gratitude to Luke Solomon, the IT guy at Burman University, as Paul and I have worked
toward fluency in the Adobe programs InDesign, Illustrator, and Photoshop. And then
there’s the standard (but no less appreciated) acknowledgment of our families and
friends who endured while we wrote this. Particular notice goes to our wives Elizabeth
George and Suzanne Mallery as well as our families for their support and encourage-
ment.
Preface xiii
Page 14
Page 15
1
Chapter 1
An Overview of IBM�
SPSS� Statistics
Introduction: An Overview of IBM SPSS
Statistics 26 and Subscription Classic
THIS BOOK gives you the step-by-step instructions necessary to do most major types
of data analysis using SPSS. The software was originally created by three Stanford
graduate students in the late 1960s. The acronym “SPSS” initially stood for “Statisti-
cal Package for the Social Sciences.” As SPSS expanded their package to address the
physical sciences and business markets, the name changed to “Statistical Product and
Service Solutions.” In 2009 IBM purchased SPSS and the name morphed to “IBM
SPSS Statistics.” SPSS is now such a standard in the industry that IBM has retained the
name due to its recognizability. No one particularly cares what the letters “SPSS” stand
for any longer. IBM SPSS Statistics is simply one of the world’s largest and most suc-
cessful statistical software companies. In this book we refer to the program as SPSS.
1.1 Necessary Skills
For this book to be effective when you conduct data analysis with SPSS, you should
have certain limited knowledge of statistics and have access to a computer that
has the necessary resources to run SPSS. Each issue is addressed in the next two
paragraphs.
STATISTICS You should have had at least a basic course in statistics or be in the
process of taking such a course. While it is true that this book devotes the first two or
three pages of each chapter to a description of the statistical procedure that follows,
these descriptions are designed to refresh the reader’s memory, not to instruct the
novice. While it is certainly possible for the novice to follow the steps in each chapter
and get SPSS to produce pages of output, a fundamental grounding in statistics is
important for an understanding of which procedures to use and what all the output
means. In addition, while the first 16 chapters should be understandable by individuals
with limited statistical background, the final 12 chapters deal with much more complex
and involved types of analyses. These chapters require substantial grounding in the
statistical techniques involved.
COMPUTER REQUIREMENTS You must:
• Have access to a personal computer that has
• Microsoft� Windows� 7 or higher; or MAC OS� 10.10 (Yosemite) or higher
installed
• IBM SPSS Statistics 26 or the Classic version of SPSS Subscription installed.
(At some point the SPSS Subscription New Interface will replace the Classic
one, but it isn’t there yet.)
Page 16
2 Chapter 1
• Know how to turn the computer on
• Have a working knowledge of the keys on the keyboard and how to use a mouse—
or other selection device such as keyboard strokes or touch screen monitors.
This book will take you the rest of the way. If you are using SPSS on a network of
computers (rather than your own PC or MAC) the steps necessary to access IBM SPSS
Statistics may vary slightly from the single step shown in the pages that follow.
1.2 Scope of Coverage
IBM SPSS Statistics is a complex and powerful statistical program by any standards.
Despite its size and complexity, SPSS and IBM have created a program that is not
only powerful but is user friendly (you’re the user; the program tries to be friendly).
By improvements over the years, SPSS has done for data analysis what Henry Ford did
for the automobile: made it available to the masses. SPSS is able to perform essentially
any type of statistical analysis ever used in the social sciences, in the business world,
and in other scientific disciplines.
This book was written for Version 26 of IBM SPSS Statistics (which is the same
as SPSS Subscription Classic as of mid-2019). With few exceptions, what you see here
will be similar to SPSS Version 16 and higher. Because only a few parts of SPSS are
changed with each version, most of this book will apply to previous versions. It’s 100%
up-to-date with Version 26, but it will lead you astray only about 2% of the time if
you’re using Version 24 or 25 and is perhaps 75% accurate for Version 16 and 50%
accurate for Version 7.0 (if you can find a computer and software that old).
Our book covers the statistical procedures present in SPSS Standard. If you are
using SPSS Base, then you will not be able to do some of the multivariate analyses
presented in the more advanced chapters. To support their program, SPSS has created
a set of comprehensive manuals. To a person fluent in statistics and data analysis, the
manuals are well written and intelligently organized. To anyone less fluent, however,
the organization is often undetectable, and the comprehensiveness (the equivalent of
almost 2,000 pages of fine-print text) is overwhelming. To the best of our knowledge,
hard-copy manuals are no longer available but most of this information may now be
accessed from SPSS as PDF downloads. The same information is also available in the
exhaustive online Help menu. Despite changes in the method of accessing this infor-
mation, for sake of simplicity we still refer to this body of information as “SPSS manu-
als” or simply “manuals.” Our book is about 400 pages long. Clearly we cannot cover in
400 pages as much material as the manuals do in 2,000, but herein lies our advantage.
The purpose of this book is to make the fundamentals of most types of data anal-
ysis clear. To create this clarity requires the omission of much (often unnecessary)
detail. Despite brevity, we have been keenly selective in what we have included and
believe that the material presented here is sufficient to provide simple instructions
that cover 95% of analyses ever conducted by researchers. Although we cannot sub-
stantiate that exact number, our time in the manuals suggests that at least 1,600 of the
2,000 pages involve detail that few researchers ever consider. How often do you really
need 7 different methods of extracting and 6 methods of rotating factors in factor anal-
ysis, or 18 different methods for post hoc comparisons after a one-way ANOVA? (By
the way, that last sentence should be understood by statistical geeks only.)
We are in no way critical of the manuals; they do well what they are designed to do
and we regard them as important adjuncts to the present book. When our space lim-
itations prevent explanation of certain details, we often refer our readers to the SPSS
manuals. Within the context of presenting a statistical procedure, we often show a win-
dow that includes several options but describe only one or two of them. This is done
without apology except for the occasional “description of these options extends beyond
Page 17
An Overview of IBM SPSS Statistics 3
the scope of this book” and cheerfully refer you to the SPSS manuals. The ultimate goal
of this format is to create clarity without sacrificing necessary detail.
1.3 Overview
This chapter introduces the major concepts discussed in this book and gives a brief over-
view of the book’s organization and the basic tools that are needed in order to use it.
If you want to run a particular statistical procedure, have used IBM SPSS Statis-
tics before, and already know which analysis you wish to conduct, you should read the
Typographical and Formatting Conventions section in this chapter (pages 5–7) and
then go to the appropriate chapter in the last portion of the book (Chapters 6 through
28). Those chapters will tell you exactly what steps you need to perform to produce the
output you desire.
If, however, you are new to IBM SPSS Statistics, then this chapter will give you
important background information that will be useful whenever you use this book.
1.4 This Book’s Organization, Chapter
by Chapter
This book was created to describe the crucial concepts of analyzing data. There are
three basic tasks associated with data analysis:
A. You must type data into the computer, and organize and format the data so both
SPSS and you can identify it easily,
B. You must tell SPSS what type of analysis you wish to conduct, and
C. You must be able to interpret what the SPSS output means.
After this introductory chapter, Chapter 2 deals with basic operations such as types of
SPSS windows, the use of the toolbar and menus, saving, viewing, and editing the out-
put, printing output, and so forth. While this chapter has been created with the begin-
ner in mind, there is much SPSS-specific information that should be useful to anyone.
Chapter 3 addresses the first step mentioned above—creating, editing, and formatting
a data file. The SPSS data editor is an instrument that makes the building, organizing,
and formatting of data files wonderfully clear and straightforward.
Chapters 4 and 5 deal with two important issues—modification and transfor-
mation of data (Chapter 4) and creation of graphs or charts (Chapter 5). Chapter 4
deals specifically with different types of data manipulation, such as creating new vari-
ables, reordering, restructuring, merging files, or selecting subsets of data for analysis.
Chapter 5 introduces the basic procedures used when making a number of different
graphs; some graphs, however, are described more fully in the later chapters.
Chapters 6 through 28 then address Steps B and C—analyzing your data and inter-
preting the output. It is important to note that each of the analysis chapters is self-con-
tained. If the beginner, for example, were instructed to conduct t tests on certain data,
Chapter 11 would give complete instructions for accomplishing that procedure. In the
Step by Step section, Step 1 is always “start the SPSS program” and refers the reader to
Chapter 2 if there are questions about how to do this. The second step is always “create
a data file or edit (if necessary) an already existing file,” and the reader is then referred
to Chapter 3 for instructions if needed. Then the steps that follow explain exactly how
to conduct a t test. Interpreting the output (Step C) involves translating the SPSS out-
put to a written narrative. We’ve used APA style throughout; if your discipline uses a
different style, it is almost certainly (95% or higher) the same as APA style.
Page 18
4 Chapter 1
As mentioned previously, this book covers SPSS Standard edition. Because some
computers at colleges or universities may not have all of these modules (the Base
module is always present), the book is organized according to the structure SPSS has
imposed: We cover most procedures included in the Base module and then selected
procedures from the more complex Advanced and Regression modules. Chapters
6–22 deal with processes included in the Base module. Chapters 23–27 deal with pro-
cedures in the Advanced Statistics and Regression modules, and Chapter 28, the anal-
ysis of residuals, draws from all three.
IBM SPSS STATISTICS BASE: Chapters 6 through 10 describe the most fundamen-
tal data analysis methods available, including frequencies, bar charts, histograms, and
percentiles (Chapter 6); descriptive statistics such as means, medians, modes, skewness,
and ranges (Chapter 7); crosstabulations and chi-square tests of independence (Chapter
8); subpopulation means (Chapter 9); and correlations between variables (Chapter 10).
The next group of chapters (Chapters 11 through 17) explains ways of testing
for differences between subgroups within your data or showing the strength of
relationships between a dependent variable and one or more independent variables
through the use of t tests (Chapter 11); ANOVAs (Chapters 12, 13, and 14); linear,
curvilinear, and multiple regression analysis (Chapters 15 and 16); and the most
common forms of nonparametric tests are discussed in Chapter 17.
Reliability analysis (Chapter 18) is a standard measure used in research that
involves multiple response measures; multidimensional scaling is designed to iden-
tify and model the structure and dimensions of a set of stimuli from dissimilarity data
(Chapter 19); and then factor analysis (Chapter 20), cluster analysis (Chapter 21), and
discriminant analysis (Chapter 22) all occupy stable and important niches in research
conducted by scientists.
IBM SPSS STANDARD: The next series of chapters deals with analyses that
involve multiple dependent variables (SPSS calls these procedures General Linear
Models; they are also commonly called MANOVAs or MANCOVAs). Included under
the heading General Linear Model are simple and general factorial models and
multivariate models (Chapter 23), and models with repeated measures or within-
subjects factors (Chapter 24).
The next three chapters deal with procedures that are only infrequently per-
formed, but they are described here because when these procedures are needed they
are indispensable. Chapter 25 describes logistic regression analysis and Chapters 26
and 27 describe hierarchical and nonhierarchical log-linear models, respectively. As
mentioned previously, Chapter 28 on residuals closes out the book.
1.5 An Introduction to the Example
A single data file is used in 17 of the first 19 chapters of this book. For more complex
procedures it has been necessary to select different data files to reflect the particular
procedures that are presented. Example data files are useful because often, things
that appear to be confusing in the SPSS documentation become quite clear when
you see an example of how they are done. Although only the most frequently used
sample data file is described here, there are a total of 12 data sets that are used to
demonstrate procedures throughout the book, in addition to data sets utilized in the
exercises. Data files are available for download at www.spss-step-by-step.net.
These files can be of substantial benefit to you as you practice some of the processes
presented here without the added burden of having to input the data. We suggest that
you make generous use of these files by trying different procedures and then com-
paring your results with those included in the output sections of different chapters.
Page 19
An Overview of IBM SPSS Statistics 5
The example has been designed so it can be used to demonstrate most of the sta-
tistical procedures presented here. It consists of a single data file used by a teacher
who teaches three sections of a class with approximately 35 students in each section.
For each student, the following information is recorded:
• ID number
• Name
• Gender
• Ethnicity
• Year in school
• Upper- or lower-division class person
• Previous GPA
• Section
• Whether or not he or she attended review sessions or did the extra credit
• The scores on five 10-point quizzes and one 75-point final exam
In Chapter 4 we describe how to create four new variables. In all presentations that fol-
low (and on the data file available on the website), these four variables are also included:
• The total number of points earned
• The final percent
• The final grade attained
• Whether the student passed or failed the course
The example data file (the entire data set is displayed at the end of Chapter 3) will also
be used as the example in the introductory chapters (Chapters 2 through 5). If you
enter the data yourself and follow the procedures described in these chapters, you will
have a working example data file identical to that used through the first half of this
book. Yes, the same material is recorded on the downloadable data files, but it may be
useful for you to practice data entry, formatting, and certain data manipulations with
this data set. If you have your own set of data to work with, all the better.
One final note: All of the data in the grades file are totally fictional, so any find-
ings exist only because we created them when we made the file.
1.6 Typographical and Formatting
Conventions
CHAPTER ORGANIZATION: Chapters 2 through 5 describe IBM SPSS Statistics
formatting and procedures, and the material covered dictates each chapter’s organi-
zation. Chapters 6 through 28 (the analysis chapters) are, with only occasional excep-
tions, organized identically. This format includes:
1. The Introduction in which the procedure that follows is described briefly and
concisely. These introductions vary in length from one to seven pages depending
on the complexity of the analysis being described.
2. The Step by Step section in which the actual steps necessary to accomplish par-
ticular analyses are presented. Most of the typographical and formatting conven-
tions described in the following pages refer to the Step by Step sections.
3. The Output section, in which the results from analyses described earlier are
displayed—often abbreviated. Text clarifies the meaning of the output, and all of
the critical output terms are defined.
Page 20
6 Chapter 1
THE SCREENS: Due to the very visual nature of SPSS, every chapter contains
pictures of screens or windows that appear on the computer monitor as you work. The
first picture from Chapter 6 (below) provides an example. These pictures are labeled
“Screens” despite the fact that sometimes what is pictured is a screen (everything that
appears on the monitor at a given time) and other times is a portion of a screen (a win-
dow, a dialog box, or something smaller). If the reader sees reference to Screen 13.3,
she knows that this is simply the third picture in Chapter 13. The screens are typically
positioned within breaks in the text (the screen icon and a title are included) and are
used for sake of reference as procedures involving that screen are described. Some-
times the screens are separate from the text and labels identify certain characteristics
of the screen (see the inside front cover for an example). Because screens take up a lot
of space, frequently-used screens are included on the inside front and back covers of
this book. At other times, within a particular chapter, a screen from a different chapter
may be cited to save space.
Screen 1.1 The Frequencies Window
Sometimes a portion of a screen or window is displayed (such as the menu bar
included here) and is embedded within the text without a label.
The Step by Step boxes: Text that surrounds the screens may designate a procedure,
but it is the Step by Step boxes that identify exactly what must be done to execute a
procedure. The following box illustrates:
Front2
In Screen
Do This
Step 3 (sample)
Front1
File
Open
Data
[or
]
grades.sav
Open
[or
grades.sav]
type
Data
Page 21
An Overview of IBM SPSS Statistics 7
Sequence Step 3 means: “Beginning with Screen 1 (displayed on the inside front cover),
click on the word File, move the cursor to Open, and then click the word Data. At this
point a new window will open (Screen 2 on the inside front cover); type ‘grades.sav’ and
then click the Open button, at which point a screen with your data file opens.” Notice
that within brackets shortcuts are sometimes suggested: Rather than the File -->
Open --> Data sequence, it is quicker to click the icon. Instead of typing grades.
sav and then clicking Open, it is quicker to double click on the grades.sav (with or
without the “.sav” suffix; this depends on your settings) file name. Items within Step
by Step boxes include:
Screens: A small screen icon will be placed to the left of each group of instruc-
tions that are based on that screen. There are three different types of screen icons:
Type of Screen Icon
Example Icon
Description of Example
Inside Cover Screens
Front1
Screen #1 on the inside front cover
General Screens
Menu
Any screen with the menu bar across the top
Graph
Any screen that displays a graph or chart
Chapter Screens
4.3
The third screen in Chapter 4
21.4
The fourth screen in Chapter 21
Other images with special meaning inside of Step by Step boxes include:
Image
What it Means
A single click of the left mouse button (or select by touch screen or key strokes)
A double-click of the left mouse button (or select by touch screen or key strokes)
A “type” icon appears before words that need to be typed
press
type
A “press” icon appears when a button such as the TAB key needs to be pressed
Proceed to the next step.
Sometimes fonts can convey information, as well:
Font
What it Means
Monospaced font
(Courier)
Any text within the boxes that is rendered in the Courier font represents text
(numbers, letters, words) to be typed into the computer (rather than being
clicked or selected).
Italicized text
Italicized text is used for information or clarifications within the Step by Step
boxes.
Bold font
The bold font is used for words that appear on the computer screen.
The groundwork is now laid. We wish you a pleasant journey through the exciting and
challenging world of data analysis!
Page 22
References
Three SPSS manuals (the three books authored by Marija
Norušis) and one SPSS syntax guide cover (in great detail)
all procedures that are included in the present book: Note:
The “19” reflects that SPSS does not seem to have more
recent manuals. These books are still available, but the
shift seems to be to have most information online.
Norušis, Marija. (2011). IBM SPSS Statistics 19 Statistical Proce-
dures Companion. Upper Saddle River, NJ: Prentice Hall.
Norušis, Marija. (2011). IBM SPSS Statistics 19 Guide to Data Analy-
sis. Upper Saddle River, NJ: Prentice Hall.
Norušis, Marija. (2011). IBM SPSS Statistics 19 Advanced Statistical
Procedures Companion. Upper Saddle River, NJ: Prentice Hall.
Collier, Jacqueline. (2009). Using SPSS Syntax: A Beginner’s Guide.
Thousand Oaks, CA: Sage Publications.
(Note: It seems that SPSS no longer publishes a syntax guide, so
we insert Collier’s work.)
Good introductory statistics texts that cover material
through Chapter 13 (one-way ANOVA) and Chapter 18
(reliability):
Fox, James; Levin, Jack; & Harkins, Stephen. (1994). Elementary
Statistics in Behavioral Research. New York: Harper Collins
College Publishers.
Hopkins, Kenneth; Glass, Gene; & Hopkins, B. R. (1995). Basic Sta-
tistics for the Behavioral Sciences. Boston: Allyn and Bacon.
Moore, David; McCabe, George; & Craig, Bruce A. (2010). Introduc-
tion to the Practice of Statistics, Third Edition. New York: W.H.
Freeman and Company.
Welkowitz, Joan; Ewen, Robert; & Cohen, Jacob. (2006). Introduc-
tory Statistics for the Behavioral Sciences, Sixth Edition. New
York: John Wiley & Sons.
Witte, Robert S. (2009). Statistics, Eighth Edition. New York: John
Wiley & Sons.
Comprehensive coverage of Analysis of Variance:
Keppel, Geoffrey, & Wickens, Thomas. (2004). Design and Analysis:
A Researcher's Handbook, Fourth Edition. Englewood Cliffs,
NJ: Prentice Hall.
Lindman, Harold R. (1992). Analysis of Variance in Experimental
Design. New York: Springer-Verlag.
Turner, J. Rick, & Thayer, Julian F. (2001). Introduction to Analy-
sis of Variance: Design, Analysis & Interpretation. Thousand
Oaks, CA: Sage Publications.
Comprehensive coverage of MANOVA and MANCOVA:
Lindman, Harold R. (1992). Analysis of Variance in Experimental
Design. New York: Springer-Verlag.
Turner, J. Rick, & Thayer, Julian F. (2001). Introduction to Analy-
sis of Variance: Design, Analysis & Interpretation. Thousand
Oaks, CA: Sage Publications.
Comprehensive coverage of simple and multiple regression
analysis:
Chatterjee, Samprit, & Hadi, Ali S. (2006). Regression Analysis by
Example, Third Edition. New York: John Wiley & Sons.
Gonick, Larry, & Smith, Woollcott. (1993). The Cartoon Guide to Sta-
tistics. New York: Harper Perennial.
Pedhazur, Elazar J. (1997). Multiple Regression in Behavioral
Research. New York: Holt, Rinehart and Winston.
Sen, Ashish, & Srivastava, Muni. (1997). Regression Analysis: The-
ory, Methods, and Applications. New York: Springer-Verlag.
Weisberg, Sanford. (2005). Applied Linear Regression, Third Edi-
tion. New York: John Wiley & Sons.
West, Stephen G., & Aiken, Leona S. (2002). Applied Multiple
Regression/Correlation Analysis for the Behavioral Sciences.
London: Routledge Academic.
Comprehensive coverage of factor analysis:
Brown, Timothy A. (2006). Confirmatory Factor Analysis for
Applied Research (Methodology In The Social Sciences). New
York: Guilford Press.
Comrey, Andrew L., & Lee, Howard B. (1992). A First Course in Fac-
tor Analysis. Hillsdale, NJ: Lawrence Erlbaum Associates.
Comprehensive coverage of cluster analysis:
Everitt, Brian S.; Landau, Sabine; & Leese, Morven. (2011). Cluster
Analysis, Fourth Edition. London: Hodder/Arnold.
Comprehensive coverage of discriminant analysis:
McLachlan, Geoffrey J. (2004). Discriminant Analysis and Statisti-
cal Pattern Recognition. New York: John Wiley & Sons.
Comprehensive coverage of nonlinear regression:
Seber, G .A. F., & Wild, C. J. (2003). Nonlinear Regression. New
York: John Wiley & Sons.
Comprehensive coverage of logistic regression analysis and
loglinear models:
Agresti, Alan. (2007). An Introduction to Categorical Data Analysis.
New York: John Wiley & Sons.
McLachlan, Geoffrey J. (2004). Discriminant Analysis and Statisti-
cal Pattern Recognition. New York: John Wiley & Sons.
Wickens, Thomas D. (1989). Multiway Contingency Tables Anal-
ysis for the Social Sciences. Hillsdale, NJ: Lawrence Erlbaum
Associates.
Comprehensive coverage of nonparametric tests:
Bagdonavius, Vilijandas; Kruopis, Julius; & Mikulin, Mikhail.
(2010). Nonparametric Tests for Complete Data. New York:
John Wiley & Sons.
Comprehensive coverage of multidimensional scaling:
Davison, M. L. (1992). Multidimensional Scaling. New York: Krieger
Publishing Company.
Young, F. W., & Hamer, R. M. (1987). Multidimensional Scaling:
History, Theory, and Applications. Hillsdale, NJ: Lawrence
Erlbaum Associates.