Sports Research with Analytical Solution Using SPSS

ISBN-13: 9781119206712 / Angielski / Twarda / 2016 / 392 str.

J. P. Verma

Opis

A step-by-step approach to problem-solving techniques using SPSS(R) in the fields of sports science and physical education Featuring a clear and accessible approach to the methods, processes, and statistical techniques used in sports science and physical education, Sports Research with Analytical Solution using SPSS(R) emphasizes how to conduct and interpret a range of statistical analysis using SPSS. The book also addresses issues faced by research scholars in these fields by providing analytical solutions to various research problems without reliance on mathematical rigor. Logically arranged to cover both fundamental and advanced concepts, the book presents standard univariate and complex multivariate statistical techniques used in sports research such as multiple regression analysis, discriminant analysis, cluster analysis, and factor analysis. The author focuses on the treatment of various parametric and nonparametric statistical tests, which are shown through the techniques and interpretations of the SPSS outputs that are generated for each analysis. Sports Research with Analytical Solution using SPSS(R) also features:

• Numerous examples and case studies to provide readers with practical applications of the analytical concepts and techniques
• Plentiful screen shots throughout to help demonstrate the implementation of SPSS outputs
• Illustrative studies with simulated realistic data to clarify the analytical techniques covered
• End-of-chapter short answer questions, multiple choice questions, assignments, and practice exercises to help build a better understanding of the presented concepts
• A companion website with associated SPSS data files and PowerPoint(R) presentations for each chapter

Sports Research with Analytical Solution using SPSS(R) is an excellent textbook for upper-undergraduate, graduate, and PhD-level courses in research methods, kinesiology, sports science, medicine, nutrition, health education, and physical education. The book is also an ideal reference for researchers and professionals in the fields of sports research, sports science, physical education, and social sciences, as well as anyone interested in learning SPSS.

Spis treści

Preface xv

About the Companion Website xviii

Acknowledgments xix

1 Introduction to Data Types and SPSS Operations 1

1.1 Introduction 1

1.2 Types of data 2

1.3 Important definitions 4

1.4 Data Cleaning 4

1.5 Detection of Errors 5

1.6 How to Start Spss? 6

1.6.1 Preparing Data File 7

1.7 Exercise 10

2 Descriptive Profile 14

2.1 Introduction 14

2.2 Explanation of Various Descriptive Statistics 16

2.3 Application of Descriptive Statistics 19

2.4 Computation of Descriptive Statistics Using Spss 25

2.5 Interpretations of the Results 29

2.6 Developing Profile Chart 31

2.7 Summary of Spss Commands 33

2.8 Exercise 33

2.9 Case Study on Descriptive Analysis 36

3 Correlation Coefficient and Partial Correlation 41

3.1 Introduction 41

3.2 Correlation Matrix and Partial Correlation 43

3.3 Application of Correlation Matrix and Partial Correlation 46

3.4 Correlation Matrix with Spss 46

3.5 Partial Correlation with Spss 51

3.6 Summary of the Spss Commands 56

3.7 Exercise 57

3.8 Case Study on Correlation 60

4 Comparing Means 65

4.1 Introduction 65

4.2 One–Sample t–Test 66

4.3 Two–Sample t–Test for Unrelated Groups 67

4.4 Paired t–Test for Related Groups 70

4.5 One–Sample t–Test with Spss 73

4.6 Two–Sample t–Test for Independent Groups with Spss 78

4.7 Paired t–Test for Related Groups with Spss 85

4.8 Summary of Spss Commands for t–Tests 90

4.9 Exercise 91

4.10 Case Study 94

5 Independent Measures Anova 100

5.1 Introduction 101

5.2 One–Way Analysis of Variance 101

5.3 One–Way Anova with Spss (Equal Sample Size) 103

5.4 One–Way Anova with Spss (Unequal Sample Size) 110

5.5 Two–Way Analysis of Variance 115

5.6 Two–Way Anova Using Spss 119

5.7 Summary of the Spss Commands 137

5.8 Exercise 138

5.9 Case Study on One–Way Anova Design 143

5.10 Case Study on Two–Way Anova  147

6 Repeated Measures Anova 153

6.1 Introduction 153

6.2 One–Way Repeated Measures Anova  154

6.3 One–Way Repeated Measures Anova Using Spss 157

6.4 Two–Way Repeated Measures Anova  166

6.5 Two–Way Repeated Measures Anova Using Spss 168

6.6 Summary of the Spss Commands for One–Way Repeated Measures Anova  182

6.7 Summary of the Spss Commands for Two–Way Repeated Measures Anova  182

6.8 Exercise 183

6.9 Case Study on Repeated Measures Design 186

7 Analysis of Covariance 190

7.1 Introduction 190

7.2 Conceptual Framework of Analysis of Covariance 191

7.3 Application of ANCOVA 192

7.4 ANCOVA with Spss 193

7.5 Summary of the Spss Commands 201

7.6 Exercise 202

7.7 Case Study on ANCOVA Design 204

8 Nonparametric Tests in Sports Research 209

8.1 Introduction 209

8.2 Chi–Square Test 211

8.3 Goodness of Fit with Spss 212

8.4 Testing Independence of Two Attributes 216

8.5 Testing Association with Spss 219

8.6 Mann Whitney U Test: Comparing Two Independent Samples 224

8.7 Wilcoxon Signed–Rank Test: For Comparing Two Related Groups 227

8.8 Kruskal Wallis Test 231

8.9 Friedman Test 234

8.10 Summary of the Spss Commands 237

8.11 Exercise 240

8.12 Case Study on Testing Independence of Attributes 243

9 Regression Analysis and Multiple Correlations 246

9.1 Introduction 246

9.2 Understanding Regression Equation 247

9.3 Application of Regression Analysis 248

9.4 Multiple Regression Analysis with Spss 249

9.5 Summary of Spss Commands for Regression Analysis 259

9.6 Exercise 259

9.7 Case Study on Regression Analysis 263

10 Application of Discriminant Function Analysis 267

10.1 Introduction 268

10.2 Basics of Discriminant Function Analysis 268

10.3 Assumptions in Discriminant Analysis 270

10.4 Why to Use Discriminant Analysis 270

10.5 Steps in Discriminant Analysis 271

10.6 Application of Discriminant Function Analysis 272

10.7 Discriminant Analysis Using Spss 274

10.8 Summary of the Spss Commands for Discriminant Analysis 284

10.9 Exercise 284

10.10 Case Study on Discriminant Analysis 288

11 Logistic Regression for Developing Logit Model in Sport 293

11.1 Introduction 293

11.2 Understanding Logistic Regression 294

11.3 Application of Logistic Regression in Sports Research 295

11.4 Assumptions in Logistic Regression 297

11.5 Steps in Developing Logistic Model 297

11.6 Logistic Analysis Using Spss 297

11.7 Interpretation of Findings 304

11.8 Summary of the Spss Commands for Logistic Regression 310

11.9 Exercise 310

11.10 Case Study on Logistic Regression 313

12 Application of Factor Analysis 319

12.1 Introduction 319

12.2 Terminologies Used in Factor Analysis 320

12.3 Assumptions in Factor Analysis 322

12.4 Steps in Factor Analysis 323

12.5 Application of Factor Analysis 323

12.6 Factor Analysis with Spss 324

12.7 Summary of the Spss Commands for Factor Analysis 336

12.8 Exercise 336

12.9 Case Study on Factor Analysis 339

Appendix 346

Bibliography 360

Index 368

O autorze

J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education.  Dr. Verma is an active researcher and expert in data analysis and sports statistics and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students in management, physical education, social science, and economics.  He is the author of seven additional books including Repeated Measures Design for Empirical Researchers and Statistics for Exercise Science and Health with Microsoft® Office Excel®, both published by Wiley.

Blurb

A step–by–step approach to problem–solving techniques using SPSS® in the fields of sports science and physical education

Featuring a clear and accessible approach to the methods, processes, and statistical techniques used in sports science and physical education, Sports Research with Analytical Solution using SPSS® emphasizes how to conduct and interpret a range of statistical analysis using SPSS. The book also addresses issues faced by research scholars in these fields by providing analytical solutions to various research problems without reliance on mathematical rigor. 

Logically arranged to cover both fundamental and advanced concepts, the book presents standard univariate and complex multivariate statistical techniques used in sports research such as multiple regression analysis, discriminant analysis, cluster analysis, and factor analysis. The author focuses on the treatment of various parametric and nonparametric statistical tests, which are shown through the techniques and interpretations of the SPSS outputs that are generated for each analysis. Sports Research with Analytical Solution using SPSS® also features:

• Numerous examples and case studies to provide readers with practical applications of the analytical concepts and techniques
• Plentiful screen shots throughout to help demonstrate the implementation of SPSS outputs
• Illustrative studies with simulated realistic data to clarify the analytical techniques covered
• End–of–chapter short answer questions, multiple choice questions, assignments, and practice exercises to help build a better understanding of the presented concepts
• A companion website with associated SPSS data files and PowerPoint® presentations for each chapter

Sports Research with Analytical Solution using SPSS® is an excellent textbook for upper–undergraduate, graduate, and PhD–level courses in research methods, kinesiology, sports science, medicine, nutrition, health education, and physical education. The book is also an ideal reference for researchers and professionals in the fields of sports research, sports science, physical education, and social sciences, as well as anyone interested in learning SPSS.