IBM SPSS Essentials: Managing and Analyzing Social Sciences Data

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.

Table of Contents:
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: χ2 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