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Sports Research with Analytical Solution using SPSS
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Main description:

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.


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.


Back cover:

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.


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.


Contents:

Preface


Chapter One: Introduction to Data and SPSS Operations


1.1 Introduction


1.2 Types of Data


1.3 Important Definitions


1.4 Data Cleaning


1.5 Detection of Errors


1.6 How to Start the SPSS


1.7 Exercise


Chapter Two: Descriptive Profile


2.1 Introduction


2.2 Explanation of Various Descriptive Statistics


2.3 Application of Descriptive Statistics


2.4 Computation of Descriptive Statistics Using SPSS


2.5 Interpretation of the Results


2.6 Developing Profile Chart


2.7 Summary of SPSS Commands


2.8 Exercise


2.9 Case Study


Chapter Three: Correlation Coefficient and Partial Correlation


3.1 Introduction


3.2 Correlation Matrix and Partial Correlation


3.3 Application of Correlation Matrix and Partial Correlation


3.4 Correlation Matrix with SPSS


3.5 Partial Correlation with SPSS


3.6 Summary of the SPSS Commands


3.7 Exercise


3.8 Case Study


Chapter Four: Comparing Means


4.1 Introduction


4.2 One–Sample t–test


4.3 Two–Sample t–test for Unrelated Groups


4.4 Paired t–test for Related Groups


4.5 One Sample t test with SPSS


4.6 Two–Sample t–test for Independent Groups with SPSS


4.7 Paired t–test for Related Groups with SPSS


4.8 Summary of SPSS Commands for t–tests


4.9 Exercise


4.10 Case Study


Chapter Five: Independent Measures ANOVA


5.1 Introduction


5.2 One–Way Analysis of Variance


5.3 One–Way ANOVA with SPSS(Equal Sample Size)


5.4 One–way ANOVA with SPSS (unequal Sample Size)


5.5 Two–Way Analysis of Variance


5.6 Two–Way ANOVA using SPSS


5.7 Summary of the SPSS Commands


5.8 Exercise


5.9 Case Study I: One Way ANOVA Design


5.10 Case Study II: Factorial Design with Two–way ANOVA


Chapter Six: Repeated Measures ANOVA


6.1 Introduction


6.2 One–way Repeated Measures ANOVA


6.3 One–Way Repeated Measures ANOVA using SPSS


6.4 Two–Way Repeated Measures ANOVA


6.5 Two–Way Repeated Measures ANOVA with SPSS


6.5.1 Computation in Two–Way Repeated Measures ANOVA


6.6 Summary of the SPSS commands for One–way Repeated Measures ANOVA


6.7 Summary of the SPSS commands for Two–way Repeated Measures ANOVA


6.8 Exercise


6.9 Case Study


Chapter Seven: Analysis of Covariance


7.1 Introduction


7.2 Conceptual Framework of Analysis of Covariance


7.3 Application of ANCOVA


7.4 Analysis of Covariance with SPSS


7.5 Summary of the SPSS Commands


7.6 Exercise


7.7 Case Study


Chapter Eight: Non Parametric Tests in Sports


8.1 Introduction


8.2 Chi–square Test


8.2.1 Testing Goodness of Fit


8.3 Goodness of Fit with SPSS


8.4 Testing Association with SPSS


8.5 Mann–Whitney U test: Comparing two independent samples


8.6 Wilcoxon Signed Rank Test: For comparing two related groups


8.7 Kruskal–Wallis Test


8.8 Friedman Test


8.9 Summary of the SPSS Commands


8.10 Exercise


8.11 Case Study


Chapter Nine: Regression Analysis and Multiple Correlations


9.1 Introduction


9.2 Understanding Regression Equation


9.3 Application of Regression Analysis


9.4 Multiple Regression Analysis with SPSS


9.5 Summary of SPSS Commands for Regression Analysis


9.6 Exercise


9.7 Case Study


Chapter Ten: Application of Discriminant Function Analysis


10.1 Introduction


10.2 Basics of Discriminant Function Analysis


10.3 Assumptions in Discriminant Analysis


10.4 Why to use Discriminant Analysis


10.5 Steps in Discriminant Analysis


10.6 Application of Discriminant Function Analysis


10.7 Discriminant Analysis using SPSS


10.8 Summary of the SPSS Commands for Discriminant Analysis


10.9 Exercise


10.10 Case Study


Chapter 11: Logistic Regression for Developing Logit model in Sport


11.1 Introduction


11.2 Understanding Logistic Regression


11.3 Application of Logistic Regression in Sports Research


11.4 Assumptions in Logistic Regression


11.5 Steps in Developing Logistic Model


11.6 Logistic Analysis using SPSS


11.7 Interpretation of Outputs


11.8 Exercise


11.9 Case Study


Chapter Twelve: Application of Factor Analysis


12.1 Introduction


12.2 Terminologies used in Factor Analysis


12.3 Assumptions in Factor Analysis


12.4 Steps in Factor Analysis


12.5 Application of Factor Analysis


12.6 Factor Analysis with SPSS


12.7 Summary of the SPSS Commands for Factor Analysis


Appendix


A.1: Table for normal distribution


A.2: Table for t–value


A.3: Table for F–value at .05 significance level


A.4: Table for F–value at .01 significance level


A.5: Table for Chi–Square


A.6: Table for Correlation Coefficient required for significance


A.7: Critical Values of Studentized Range Distribution (q) for Familywise ALPHA = .05


References


Index


PRODUCT DETAILS

ISBN-13: 9781119206729
Publisher: John Wiley & Sons Ltd (Wiley–Blackwell)
Publication date: April, 2016
Pages: 416

Subcategories: Sports Medicine