John Wiley & Sons IBM SPSS Essentials Cover Master the fundamentals of SPSS with this newly updated and instructive resource The newly and thor.. Product #: 978-1-119-41742-2 Regular price: $69.07 $69.07 In Stock

IBM SPSS Essentials

Managing and Analyzing Social Sciences Data

Kulas, John T. / Prieto Palacios Roji, Renata Garcia / Smith, Adam M.

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2. Edition June 2021
288 Pages, Softcover
Wiley & Sons Ltd

ISBN: 978-1-119-41742-2
John Wiley & Sons

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Master the fundamentals of SPSS with this newly updated and instructive resource

The newly and thoroughly revised Second Edition of SPSS Essentials delivers a comprehensive guide for students in the social sciences who wish to learn how to use the Statistical Package for the Social Sciences (SPSS) for the effective collection, management, and analysis of data. The accomplished researchers and authors provide readers with the practical nuts and bolts of SPSS usage and data entry, with a particular emphasis on managing and manipulating data.

The book offers an introduction to SPSS, how to navigate it, and a discussion of how to understand the data the reader is working with. It also covers inferential statistics, including topics like hypothesis testing, one-sample Z-testing, T-testing, ANOVAs, correlations, and regression. Five unique appendices round out the text, providing readers with discussions of dealing with real-world data, troubleshooting, advanced data manipulations, and new workbook activities.

SPSS Essentials offers a wide variety of features, including:
* A revised chapter order, designed to match the pacing and content of typical undergraduate statistics classes
* An explanation of when particular inferential statistics are appropriate for use, given the nature of the data being worked with
* Additional material on understanding your data sample, including discussions of SPSS output and how to find the most relevant information
* A companion website offering additional problem sets, complete with answers

Perfect for undergraduate students of the social sciences who are just getting started with SPSS, SPSS Essentials also belongs on the bookshelves of advanced placement high school students and practitioners in social science who want to brush up on the fundamentals of this powerful and flexible software package.

Preface xiii

Acknowledgments xvii

Author Biography xix

Part I Introduction 1

1 What is SPSS? 3

Chapter Learning Objectives 3

What Is SPSS Used For 4

The Power of SPSS 5

SPSS Compared to Other Programs 5

Summary 6

Key Terms 6

Discussion Questions 6

2 Navigating SPSS 7

Chapter Learning Objectives 7

How the Program Works 7

Important File Types 8

Data Files 8

Syntax Files 10

Output Files 10

The "Others" 11

Managing Your SPSS Life 11

The Importance of Maintaining the Raw Data as an "Untouched" File 12

Summary 13

Key Terms 13

Discussion Questions 13

3 Introduction to Data 15

Chapter Learning Objectives 15

Understanding Your Data 16

Independent Versus Dependent Variables 16

Scales of Measurement 16

The SPSS Data Perspective 17

Data Represented by Numbers (Numeric) 17

Data Represented by Words (String) 18

The Other Variable Types 18

Your Data in SPSS - Think Matrices 19

Summary 20

Key Terms 21

Discussion Questions 21

4 Getting Your Data into SPSS 23

Chapter Learning Objectives 23

Before SPSS 24

Specifying Operations Through SPSS 25

Creating a Data Shell 25

Creating Data Files Via Syntax 28

Numeric Versus String Variables 29

Data Entry Within the Syntax File 31

"Saving" Populated Datafiles 33

Having SPSS Auto-Generate Your Syntax 34

Controlling Your "Open" Datafiles 35

Summary 37

Key Terms 38

Discussion Questions 39

References 39

5 Accessing Your Data 41

Chapter Learning Objectives 41

Accessing Your Data Files 42

Get File and Save Outfile 43

Creating Subsets of Data 44

Importing Data from Excel 44

Using the Import Data Wizard 45

The Copy-Paste "Option" (aka This Is a Terrible Idea) 47

Summary 48

Key Terms 48

Discussion Questions 48

6 Defining Your Data 49

Chapter Learning Objectives 49

Annotation 50

Defining Your Dataset 51

Adding Variable Labels 51

Adding Value Labels 52

Summary 54

Key Terms 55

Discussion Questions 55

Part II Statistics 57

7 Descriptive Statistics 59

Chapter Learning Objectives 59

Frequencies 60

Displaying Data Graphically 62

Location and Spread 63

Descriptive Statistics 65

Measures of Central Tendency and Variability 65

A General Note on Analyses 67

A General Note About Output Files 68

Summary 68

Key Terms 68

Discussion Questions 69

8 Hypothesis Testing 71

Chapter Learning Objectives 71

Descriptive Versus Inferential Statistics 72

Hypothesis Testing (A Process for Interpreting Inferential Statistics) 72

Six Steps of Hypothesis Testing 73

Summary 75

Key Terms 75

Discussion Questions 76

9 Z-and T-Tests 77

Chapter Learning Objectives 77

The One Sample Z-Test 78

The t-Test 80

One-Sample T-Test 80

Two Independent Samples T-Test 84

Two Correlated/Paired Samples T-Test 88

Summary 93

Key Terms 93

Discussion Questions 94

10 Inferential Analyses (ANOVAs) 97

Chapter Learning Objectives 97

One-Way ANOVA (One-Way Command) 98

Repeated-Measures ANOVA (GLM Command) 101

Factorial ANOVA (Unianova Command) 109

Follow-Up Contrasts 113

Summary 113

Key Terms 114

Discussion Questions 115

Reference 116

11 Inferential Analyses (Correlation or Regression) 117

Chapter Learning Objectives 117

Correlation 118

Simple Regression 122

Multiple Regression 125

Straight Regression 126

Hierarchical Regression 130

Visualizing Your Relationship 135

Summary 137

Key Terms 137

Discussion Questions 138

12 Nonparametric Analyses 141

Chapter Learning Objectives 141

Parametric Versus Nonparametric Analyses 141

"The" (Pearson's) Chi-Square: chi2 143

Two Variable Example 146

Summary 150

Key Terms 150

Discussion Questions 151

Part III Advanced Data Management 153

13 Manipulating Your Data 155

Chapter Learning Objectives 155

Creating Scale Scores 156

How SPSS Thinks About Data 156

Recoding Your Data 157

Creating Your Scales 157

The Importance of Selecting All 161

Summary 167

Key Terms 167

Discussion Questions 167

14 Collapsing and Merging Data Files 169

Chapter Learning Objectives 169

Same People, Different Information 170

Different People, Same Information 175

Summary 177

Key Terms 177

Discussion Questions 178

15 Differential Treatment of Your Data 179

Chapter Learning Objectives 179

Isolating Interesting Cases 180

Creating a New Data File 180

Splitting Files 184

Summary 188

Key Terms 188

Discussion Questions 188

16 Using Your Output 189

Chapter Learning Objectives 189

Problem Solving 190

Spaces in All the Wrong Places 190

Column Information 195

There Is One Little Thing... 198

Maximizing Output Information 199

Summary 200

Key Terms 201

Discussion Questions 201

17 Other Tricks of the Trade 203

Chapter Learning Objectives 203

Salvaging Old Syntax 204

The Importance of Notepad 204

Tricking SPSS To "Think" Across Rows 210

Transposing Your Matrix 210

Aggregating Your Files 211

"Do If" and "End If" 215

Summary 218

Key Terms 219

Discussion Questions 219

Appendix A: Completed Questionnaire Form Example 221

Appendix B: Example Code Sheet for Questionnaire 227

Appendix C: Summary of Creating and Defining a Data File 233

Appendix D: Example Syntax File Integrating Multiple Commands (Fulfilling Multiple Purposes) 239

Appendix E: Commands To Know, Organized By Importance 249

Answers to Chapter Discussion Questions 251

Index 263
JOHN T. KULAS, PhD, is a Professor of Industrial and Organizational Psychology at Montclair State University in Montclair, NJ, United States.

RENATA GARCIA PRIETO PALACIOS ROJI, MA, is a PhD candidate in Industrial and Organizational Psychology at Montclair State University in Montclair, NJ, United States.

ADAM M. SMITH, PhD, is an associate consultant at Kincentric and adjunct instructor at Wentworth Institute of Technology and Harvard University.

J. T. Kulas, Northern Illinois University, USA; R. G. Prieto Palacios Roji, Montclair State University, USA; A. M. Smith, Auburn University, USA