IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference

by Darren George, Paul Mallery

Overview

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth 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. 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 multidimensional 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. The end sections include a description of data files used in exercises, an exhaustive glossary, suggestions for further reading, and a comprehensive index.

IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an 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 27
• A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection.

Product Details

ISBN-13:	9781032070940
Publisher:	Taylor & Francis
Publication date:	12/29/2021
Edition description:	17th ed.
Pages:	418
Product dimensions:	8.25(w) x 11.00(h) x (d)

About the Author

Darren George teaches at the University of Alabama. His research focuses on intimate relationships and optimal performance. He teaches classes in research methodology, statistics, personality/social psychology, and sport and performance psychology.

Paul Mallery is a Professor of Psychology at La Sierra University whose research focuses on the intersection of religion and prejudice. He teaches classes in research methodology, statistics, social psychology, and political psychology.

Table of Contents

Preface xii

1 An Overview of IBM® SPSS® Statistics 1

Introduction: An Overview of IBM SPSS Statistics 27 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 33

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

9 The Means Procedure 132

9.1 Step by Step 132

9.2 Printing Results 136

9.3 Output 136

Exercises 138

10 A Priori Power Analysis: What Sample Size Do I Need? 139

10.1 One-Sample t Test 141

10.2 Independent-Samples t Test 142

10.3 Paired-Samples t Test 143

10.4 One-Way ANOVA 144

10.5 Correlation 146

10.6 Regression 147

10.7 Printing Results 148

Exercises 149

11 Bivariate Correlation 151

11.1 What is a Correlation? 151

11.2 Additional Considerations 153

11.3 Step by Step 154

11.4 Printing Results 158

11.5 Output 159

Exercises 160

12 The t Test Procedure 161

12.1 Independent-Samples t Tests 161

12.2 Paired-Samples t Tests 161

12.3 One-Sample t Tests 162

12.4 Significance and Effect Size 162

12.5 Step by Step 163

12.6 Printing Results 167

12.7 Output 168

Exercises 171

What is Bootstrapping? 172

13 The One-Way ANOVA Procedure 173

13.1 Introduction to One-Way Analysis of Variance 173

13.2 Step by Step 174

13.3 Printing Results 179

13.4 Output 179

Exercises 183

14 General Linear Model: Two-Way ANOVA 185

14.1 Statistical Power 185

14.2 Two-Way Analysis of Variance 186

14.3 Step by Step 187

14.4 Printing Results 190

14.5 Output 190

Exercises 192

15 General Linear Model: Three-Way ANOVA 193

15.1 Three-Way Analysis of Variance 193

15.2 The Influence of Covariates 194

15.3 Step by Step 195

15.4 Printing Results 197

15.5 Output 197

15.6 A Three-Way ANOVA that Includes a Covariate 202

Exercises 206

16 Simple Linear Regression 209

16.1 Predicted Values and the Regression Equation 209

16.2 Simple Regression and the Amount of Variance Explained 211

16.3 Testing for a Curvilinear Relationship 211

16.4 Step by Step 214

16.5 Printing Results 218

16.6 Output 219

16.7 A Regression Analysis that Tests for a Curvilinear Trend 220

Exercises 221

17 Multiple Regression Analysis 224

17.1 The Regression Equation 224

17.2 Regression and R²: The Amount of Variance Explained 226

17.3 Curvilinear Trends, Model Building, and References 226

17.4 Step by Step 228

17.5 Printing Results 233

17.6 Output 233

17.7 Change of Values as Each new Variable is Added 234

Exercises 237

18 Nonparametric Procedures 238

18.1 Step by Step 239

18.2 Are Observed Values Distributed Differently than a Hypothesized Distribution? 241

18.3 Is the Order of Observed Values Non-Random? 243

18.4 Is a Continuous Variable Different in Different Groups? 244

18.5 Are the Medians of a Variable Different for Different Groups? 246

18.6 Are My Within-Subjects (Dependent Samples or Repeated Measures) Measurements Different? 247

18.7 Printing Results 250

19 Reliability Analysis 251

19.1 Coefficient Alpha (α) 252

19.2 Split-Half Reliability 252

19.3 The Example 252

19.4 Step by Step 253

19.5 Printing Results 257

19.6 Output 257

Exercises 262

20 Multidimensional Scaling 263

20.1 Square Asymmetrical Matrixes (The Sociogram Example) 264

20.2 Step by Step 265

20.3 Printing Results 271

20.4 Output 271

21 Factor Analysis 274

21.1 Create a Correlation Matrix 274

21.2 Factor Extraction 274

21.3 Factor Selection and Rotation 275

21.4 Interpretation 277

21.5 Step by Step 278

21.6 Output 284

22 Cluster Analysis 287

22.1 Cluster Analysis and Factor Analysis Contrasted 287

22.2 Procedures for Conducting Cluster Analysis 288

22.3 Step by Step 290

22.4 Printing Results 296

22.5 Output 296

23 Discriminant Analysis 301

23.1 The Example: Admission into a Graduate Program 302

23.2 The Steps Used in Discriminant Analysis 302

23.3 Step by Step 304

23.4 Output 309

24 General Linear Models: MANOVA and MANCOVA 316

24.1 Step by Step 317

24.2 Printing Results 324

24.3 Output 325

Exercises 330

25 G.L.M.: Repeated-Measures MANOVA 331

25.1 Step by Step 332

25.2 Printing Results 337

25.3 Output 337

Exercises 341

26 Logistic Regression 342

26.1 The Math of Logistic Regression 342

26.2 Step by Step 343

26.3 Printing Results 347

26.4 Output 348

27 Hierarchical Log-Linear Models 352

27.1 Log-Linear Models 352

27.2 The Model Selection Log-Linear Procedure 353

27.3 Step by Step 354

27.4 Printing Results 358

27.5 Output 358

28 Nonhierarchical Log-Linear Models 364

28.1 Models 364

28.2 A Few Words about Model Selection 365

28.3 Types of Models Beyond the Scope of This Chapter 365

28.4 Step by Step 366

28.5 Printing Results 370

28.6 Output 370

29 Residuals: Analyzing Left-Over Variance 373

29.1 Residuals 373

29.2 Linear Regression: A Case Study 374

29.3 General Log-Linear Models: A Case Study 376

29.4 Accessing Residuals in SPSS 380

Data Files 383

Glossary 387

References 393

Credits 395

Index 397