IBM SPSS Statistics 25 Step by Step

A Simple Guide and Reference

Darren George, Paul Mallery

• Publisher: Routledge
• Year: 2018
• eBook ISBN: 9781351033886
• Edition: 15
• Topic: Education
• Subtopic: Education Technology

IBM SPSS Statistics 25 Step by Step: A Simple Guide and Reference, fifteenth edition, takes a straightforward, 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. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS.

This book covers both the basics of descriptive statistical analysis using SPSS through to more advanced topics such as multiple regression, multidimensional scaling and MANOVA, including instructions for Windows and Mac. This makes it ideal for both undergraduate statistics courses and for postgraduates looking to further develop their statistics and SPSS knowledge.

New to this edition:

• Updated throughout to SPSS 25

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• Updated / restructured material on: Chart Builder; Univariate ANOVA; moderation on two- and three-way ANOVA; and Factor Analytic Techniques (formerly Factor Analysis structure)

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• New material on computing z and T scores, and on computing z scores within descriptive statistics

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• Clearer in-chapter links between the type of data and type of research question that the procedure can answer

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• Updated / additional datasets, exercises, and expanded Companion Website material, including Powerpoint slides for instructors

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Chapter 1
An Overview of IBM^® SPSS^® Statistics

Introduction: An Overview of IBM SPSS Statistics 25

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 “Statistical Package for the Social Sciences.” As SPSS expanded their package to address the hard 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 successful 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 Vista® or Windows® 7 or 8.1 or 10; MAC OS® 10.8 (Mountain Lion) or higher installed

• IBM SPSS Statistics 25.0 installed

• 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. The software occupies about 800 MB of your hard drive and requires at least 1 GB of RAM to operate adequately. Despite its size and complexity, SPSS has 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 25 of IBM SPSS Statistics. More specifically, the screen shots and output are based on Version 23.0. With some exceptions, what you see here will be similar to SPSS Version 7.0 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 25.0, but it will lead you astray only about 2% of the time if you’re using Version 23 or 24 and is perhaps 60% accurate for Version 7.0 (if you can find a computer and software that old).

Our book covers the statistical procedures present in three of the modules created by SPSS that are most frequently used by researchers. A module (within the SPSS context) is simply a set of different statistical operations. We include the Base module (technically called IBM SPSS Statistics Base), the module covering advanced statistics (IBM SPSS Advanced Statistics), and the module that addresses regression models (IBM SPSS Regression)—all described in greater detail later in this chapter. To support their program, SPSS has created a set of comprehensive manuals that cover all procedures these three modules are designed to perform. 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 information, for sake of simplicity we still refer to this body of information as “SPSS manuals” 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 analysis 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 substantiate 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 analysis, 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 limitations 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 window 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 the scope of this book” and cheerfully refer you to the appropriate SPSS manual. 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 overview 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 Statistics 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...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication Page
• Table of Contents
• Preface
• 1 An Overview of IBM® SPSS® Statistics
• 2A IBM SPSS Statistics Processes for PC
• 2B IBM SPSS Statistics Processes for Mac
• 3 Creating and Editing a Data File
• 4 Managing Data
• 5 Graphs and Charts: Creating and Editing
• 6 Frequencies
• 7 Descriptive Statistics
• 8 Crosstabulation and χ2 Analyses
• 9 The Means Procedure
• 10 Bivariate Correlation
• 11 The t Test Procedure
• 12 The One-Way ANOVA Procedure
• 13 General Linear Model: Two-Way ANOVA
• 14 General Linear Model: Three-Way ANOVA
• 15 Simple Linear Regression
• 16 Multiple Regression Analysis
• 17 Nonparametric Procedures
• 18 Reliability Analysis
• 19 Multidimensional Scaling
• 20 Factor Analysis
• 21 Cluster Analysis
• 22 Discriminant Analysis
• 23 General Linear Models: MANOVA and MANCOVA
• 24 G.L.M.: Repeated-Measures Measures MANOVA
• 25 Logistic Regression
• 26 Hierarchical Log-Linear Models
• 27 Nonhierarchical Log-Linear Models
• 28 Residuals: Analyzing Left-Over Variance
• Data Files
• Glossary
• References
• Credit
• Index