How to Use Multivariate Statistics in Descriptive Research - Gary J Conti

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Résumé :

Reveal hidden patterns in your data using multivariate descriptive analysis

Many researchers believe multivariate statistics belong only to inferential research, leaving powerful analytical tools unused in descriptive studies. How to Use Multivariate Statistics in Descriptive Research: Making the Invisible Visible challenges this assumption directly, demonstrating how factor analysis, cluster analysis, and discriminant analysis can expose patterns and relationships that simpler methods overlook - transforming how social and behavioral scientists understand their data.

Written in clear, practical language, this book provides step-by-step instructions for conducting multivariate analyses using SPSS, R, and Excel. Each chapter features real-world illustrations that ground abstract concepts in concrete applications. Reflective sections titled Revealing the Opening Quote connect statistical insights to broader understanding, helping readers see beyond numbers to meaningful interpretation.

Readers will also find:

• Detailed guidance on applying factor analysis to identify underlying constructs within complex descriptive datasets and research questions
• Cluster analysis techniques that group observations based on shared characteristics, revealing natural patterns invisible to univariate approaches
• Discriminant analysis methods that classify cases and predict group membership using multiple variables simultaneously for clearer interpretation
• Practical software tutorials walking through each statistical procedure in SPSS, R, and Excel with reproducible examples
• Chapter-ending reflections that bridge statistical technique to conceptual understanding, reinforcing both mechanical skill and interpretive insight

Designed for educators, graduate students, and researchers in the social and behavioral sciences, this book empowers readers to move beyond basic descriptive statistics. By mastering multivariate techniques, researchers gain the ability to detect hidden structures in their data and communicate findings with greater precision and confidence....

Biographie:

Dr. Gary J. Conti is an experienced researcher and educator specializing in multivariate statistical methods for the social and behavioral sciences....

Sommaire:

Preface xiii

Acknowledgments xv

Introduction 1

Section One a New Perspective on Descriptive Research 5

1 Reframing Your Perspectives 7

Introduction 7

Our Journey to Reframing 9

Note About References 11

Revealing the Opening Quote 12

2 Descriptive Research 14

Research Design 14

Descriptive Research 15

Revealing the Opening Quote 16

3 Statistics 17

Essential Concepts 17

Multivariate vs Univariate 18

Descriptive Statistics 20

Other Statistics for Beating Up on Data 21

Revealing the Opening Quote 24

Section Two Procedures for Making the Invisible Visible 27

4 Discriminant Analysis 33

Introduction 33

What Is Discriminant Analysis? 34

Establishing Groups 35

Hypotheses and Criteria for Evaluation 35

Understanding the Output 36

Assumptions and Related Methods 36

Describing Groups with Discriminant Analysis 37

The Role of the Structure Matrix 37

The Role of Group Means 38

An Example 38

Conclusion 40

5 Computing Discriminant Analysis 41

Introduction 41

SPSS Commands 41

Menu Commands for Discriminant Analysis 41

Syntax Commands for Discriminant Analysis 45

R Coding 46

R Code for Discriminant Analysis 47

Stepwise Discriminant Analysis in R: A Cautionary Note 48

Excel Procedures 48

Using XLSTAT 48

Manual Steps in Excel (Approximated) 49

Revealing the Opening Quote 49

6 Cluster Analysis 51

Introduction 51

Cluster Analysis 52

Other Clustering Methods 54

Interpreting the Clusters 55

Describing with Cluster Analysis 55

7 Computing Cluster Analysis 61

SPSS Commands 61

Menu Commands for Cluster Analysis 61

Syntax Commands for Cluster Analysis 67

Commands for Quick Cluster 68

R Coding 68

R Code for Cluster Analysis 68

Customizing and Troubleshooting the Clustering and Frequency Codes in R 70

Excel Procedures 72

Excel's Capabilities for Cluster Analysis 72

The Power of R: A Free, Open- Source Alternative 73

Conclusion: Best of Both Worlds 74

Revealing the Opening Quote 74

8 Factor Analysis 75

Introduction 75

Introducing Factor Analysis 75

Determining the Number of Factors 78

Naming the Factors 81

Conducting a Factor Analysis 83

Step 1: Initiating the Analysis 84

Step 2: Extracting Factors 85

Step 3: Rotating the Factors 86

Concluding Phase: The Grand Finale! 87

Describing with Factor Analysis 88

Conclusion 92

9 Computing Factor Analysis 93

SPSS Commands 93

Menu Commands for Factor Analysis 93

Syntax Commands for Factor Analysis 99

R Coding 101

R Code for Factor Analysis 101

Adjusting Parameters 102

Reading Data from Excel 102

Excel Procedures 102

Background 102

Steps for Running Excel 103

Limitations of Factor Analysis in Excel 106

Summary 106

Example of Excel Workflow 106

Revealing the Opening Quote 106

Section Three Multivariate Procedures in Action 109

10 The Questionnaire 111

Questionnaires 111

Using Factor Analysis 112

An Example 114

Constructing the Questionnaire 114

Applying Factor Analysis 114

Excerpt: Factor Analysis 115

Revealing the Opening Quote 123

11 Building Synergy: Combining Factor, Cluster, and Discriminant Analysis in Descriptive Research 124

Introduction 124

Q...