Sports Research with Analytical Solution using 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.

• Preface xvAbout the Companion Website xviiiAcknowledgments xix1 Introduction to Data Types and SPSS Operations 11.1 Introduction 11.2 Types of data 21.2.1 Qualitative Data 21.2.2 Quantitative Data 31.3 Important definitions 41.3.1 Variable 41.4 Data Cleaning 41.5 Detection of Errors 51.5.1 Using Frequencies 51.5.2 Using Mean and Standard Deviation 51.5.3 Logic Checks 51.5.4 Outlier Detection 51.6 How to Start Spss? 61.6.1 Preparing Data File 71.7 Exercise 101.7.1 Short Answer Questions 101.7.2 Multiple Choice Questions 112 Descriptive Profile 142.1 Introduction 142.2 Explanation of Various Descriptive Statistics 162.2.1 Mean 162.2.2 Variance 162.2.3 Standard Error of Mean 172.2.4 Skewness 172.2.5 Kurtosis 182.2.6 Percentiles 192.3 Application of Descriptive Statistics 192.3.1 Testing Normality of Data and Identifying Outliers 202.4 Computation of Descriptive Statistics Using Spss 252.4.1 Preparation of Data File 252.4.2 Defining Variables 262.4.3 Entering Data 262.4.4 SPSS Commands 262.5 Interpretations of the Results 292.6 Developing Profile Chart 312.7 Summary of Spss Commands 332.8 Exercise 332.8.1 Short Answer Questions 332.8.2 Multiple Choice Questions 342.9 Case Study on Descriptive Analysis 363 Correlation Coefficient and Partial Correlation 413.1 Introduction 413.2 Correlation Matrix and Partial Correlation 433.2.1 Product Moment Correlation Coefficient 433.2.2 Partial Correlation 453.3 Application of Correlation Matrix and Partial Correlation 463.4 Correlation Matrix with Spss 463.4.1 Computation in Correlation Matrix 463.4.2 Interpretations of Findings 513.5 Partial Correlation with Spss 513.5.1 Computation of Partial Correlations 523.5.2 Interpretation of Partial Correlation 553.6 Summary of the Spss Commands 563.6.1 For Computing Correlation Matrix 563.6.2 For Computing Partial Correlations 573.7 Exercise 573.7.1 Short Answer Questions 573.7.2 Multiple Choice Questions 573.7.3 Assignment 603.8 Case Study on Correlation 604 Comparing Means 654.1 Introduction 654.2 One‐Sample t‐Test 664.2.1 Application of One‐Sample t‐Test 674.3 Two‐Sample t‐Test for Unrelated Groups 674.3.1 Assumptions While Using t‐Test 674.3.2 Case I: Two‐Tailed Test 684.3.3 Case II: Right Tailed Test 684.3.4 Case III: Left Tailed Test 694.3.5 Application of Two‐Sample t-Test 704.4 Paired t‐Test for Related Groups 704.4.1 Case I: Two‐Tailed Test 714.4.2 Case II: Right Tailed Test 714.4.3 Case III: Left Tailed Test 724.4.4 Application of Paired t‐Test 734.5 One‐Sample t‐Test with Spss 734.5.1 Computation in t‐Test for Single Group 744.5.2 Interpretation of Findings 774.6 Two‐Sample t‐Test for Independent Groups with Spss 784.6.1 Computation in Two‐Sample t‐Test 794.6.2 Interpretation of Findings 834.7 Paired t‐Test for Related Groups with Spss 854.7.1 Computation in Paired t‐Test 864.7.2 Interpretation of Findings 894.8 Summary of Spss Commands for t‐Tests 904.8.1 One‐Sample t‐Test 904.8.2 Two‐Sample t‐Test for Independent Groups 904.8.3 Paired t‐Test 914.9 Exercise 914.9.1 Short Answer Questions 914.9.2 Multiple Choice Questions 914.9.3 Assignment 934.10 Case Study 945 Independent Measures Anova 1005.1 Introduction 1015.2 One‐Way Analysis of Variance 1015.2.1 One‐Way ANOVA Model 1025.2.2 Post Hoc Test 1025.2.3 Application of One‐Way ANOVA 1035.3 One‐Way Anova with Spss (Equal Sample Size) 1035.3.1 Computation in One‐Way ANOVA (Equal Sample Size) 1045.3.2 Interpretation of Findings 1075.4 One‐Way Anova with Spss (Unequal Sample Size) 1105.4.1 Computation in One‐Way ANOVA (Unequal Sample Size) 1115.4.2 Interpretation of Findings 1145.5 Two‐Way Analysis of Variance 1155.5.1 Assumptions in Two‐Way Analysis of Variance 1165.5.2 Hypotheses in Two‐Way ANOVA 1165.5.3 Factors 1175.5.4 Treatment Groups 1175.5.5 Main Effect 1175.5.6 Interaction Effect 1175.5.7 Within‐Groups Variation 1175.5.8 F‐Statistic 1175.5.9 Two‐Way ANOVA Table 1185.5.10 Interpretation 1185.5.11 Application of Two‐Way Analysis of Variance 1185.6 Two‐Way Anova Using Spss 1195.6.1 Computation in Two‐Way ANOVA 1215.6.2 Interpretation of Findings 1265.7 Summary of the Spss Commands 1375.7.1 One‐Way ANOVA 1375.7.2 Two‐Way ANOVA 1385.8 Exercise 1385.8.1 Short Answer Questions 1385.8.2 Multiple Choice Questions 1395.8.3 Assignment 1425.9 Case Study on One‐Way Anova Design 1435.10 Case Study on Two‐Way Anova 1476 Repeated Measures Anova 1536.1 Introduction 1536.2 One‐Way Repeated Measures Anova 1546.2.1 Assumptions in One‐Way Repeated Measures ANOVA 1556.2.2 Application in Sports Research 1556.2.3 Steps in Solving One‐Way Repeated Measures ANOVA 1566.3 One‐Way Repeated Measures Anova Using Spss 1576.3.1 Computation in the One‐Way Repeated Measures ANOVA 1576.3.2 Interpretation of Findings 1616.3.3 Findings of the Study 1656.3.4 Inference 1666.4 Two‐Way Repeated Measures Anova 1666.4.1 Assumptions in Two‐Way Repeated Measures ANOVA 1666.4.2 Application in Sports Research 1676.4.3 Steps in Solving Two‐Way Repeated Measures ANOVA 1676.5 Two‐Way Repeated Measures Anova Using Spss 1686.5.1 Computation in Two‐Way Repeated Measures ANOVA 1706.5.2 Interpretation of Findings 1736.5.3 Findings of the Study 1816.5.4 Inference 1816.6 Summary of the Spss Commands for One‐Way Repeated Measures Anova 1826.7 Summary of the Spss Commands for Two‐Way Repeated Measures Anova 1826.8 Exercise 1836.8.1 Short Answer Questions 1836.8.2 Multiple Choice Questions 1836.8.3 Assignment 1856.9 Case Study on Repeated Measures Design 1867 Analysis of Covariance 1907.1 Introduction 1907.2 Conceptual Framework of Analysis of Covariance 1917.3 Application of ANCOVA 1927.4 ANCOVA with Spss 1937.4.1 Computation in ANCOVA 1947.5 Summary of the Spss Commands 2017.6 Exercise 2027.6.1 Short Answer Questions 2027.6.2 Multiple Choice Questions 2027.6.3 Assignment 2037.7 Case Study on ANCOVA Design 2048 Nonparametric Tests in Sports Research 2098.1 Introduction 2098.2 Chi‐Square Test 2118.2.1 Testing Goodness of Fit 2118.2.2 Yates’ Correction 2128.2.3 Contingency Coefficient 2128.3 Goodness of Fit with Spss 2128.3.1 Computation in Goodness of Fit 2138.3.2 Interpretation of Findings 2168.4 Testing Independence of Two Attributes 2168.4.1 Interpretation 2188.5 Testing Association with Spss 2198.5.1 Computation in Chi‐Square 2198.5.2 Interpretation of Findings 2238.6 Mann–Whitney U Test: Comparing Two Independent Samples 2248.6.1 Computation in Mann–Whitney U Statistic Using SPSS 2248.6.2 Interpretation of Findings 2268.7 Wilcoxon Signed‐Rank Test: For Comparing Two Related Groups 2278.7.1 Computation in Wilcoxon Signed‐Rank Test Using SPSS 2288.7.2 Interpretation of Findings 2308.8 Kruskal–Wallis Test 2318.8.1 Computation in Kruskal–Wallis Test Using SPSS 2328.8.2 Interpretation of Findings 2348.9 Friedman Test 2348.9.1 Computation in Friedman Test Using SPSS 2358.9.2 Interpretation of Findings 2378.10 Summary of the Spss Commands 2378.10.1 Computing Chi‐Square Statistic (for Testing Goodness of Fit) 2378.10.2 Computing Chi‐Square Statistic (for Testing Independence) 2388.10.3 Computation in Mann–Whitney U Test 2388.10.4 Computation in Wilcoxon Signed‐Rank Test 2398.10.5 Computation in Kruskal–Wallis Test 2398.10.6 Computation in Friedman Test 2398.11 Exercise 2408.11.1 Short Answer Questions 2408.11.2 Multiple Choice Questions 2418.11.3 Assignment 2438.12 Case Study on Testing Independence of Attributes 2439 Regression Analysis and Multiple Correlations 2469.1 Introduction 2469.2 Understanding Regression Equation 2479.2.1 Methods of Regression Analysis 2479.2.2 Multiple Correlation 2489.3 Application of Regression Analysis 2489.4 Multiple Regression Analysis with Spss 2499.4.1 Computation in Regression Analysis 2499.4.2 Interpretation of Findings 2549.5 Summary of Spss Commands for Regression Analysis 2599.6 Exercise 2599.6.1 Short Answer Questions 2599.6.2 Multiple Choice Questions 2609.6.3 Assignment 2619.7 Case Study on Regression Analysis 26310 Application of Discriminant Function Analysis 26710.1 Introduction 26810.2 Basics of Discriminant Function Analysis 26810.2.1 Discriminating Variables 26810.2.2 Dependent Variable 26810.2.3 Discriminant Function 26810.2.4 Classification Matrix 26910.2.5 Stepwise Method of Discriminant Analysis 26910.2.6 Power of Discriminating Variable 26910.2.7 Canonical Correlation 26910.2.8 Wilks’ Lambda 27010.3 Assumptions in Discriminant Analysis 27010.4 Why to Use Discriminant Analysis 27010.5 Steps in Discriminant Analysis 27110.6 Application of Discriminant Function Analysis 27210.7 Discriminant Analysis Using Spss 27410.7.1 Computation in Discriminant Analysis 27410.7.2 Interpretation of Findings 27910.8 Summary of the Spss Commands for Discriminant Analysis 28410.9 Exercise 28410.9.1 Short Answer Questions 28410.9.2 Multiple Choice Questions 28510.9.3 Assignment 28610.10 Case Study on Discriminant Analysis 28811 Logistic Regression for Developing Logit Model in Sport 29311.1 Introduction 29311.2 Understanding Logistic Regression 29411.3 Application of Logistic Regression in Sports Research 29511.4 Assumptions in Logistic Regression 29711.5 Steps in Developing Logistic Model 29711.6 Logistic Analysis Using Spss 29711.6.1 Block 0 29911.6.2 Block 1 29911.6.3 Computation in Logistic Regression with SPSS 29911.7 Interpretation of Findings 30411.7.1 Case Processing and Coding Summary 30411.7.2 Analyzing Logistic Models 30511.8 Summary of the Spss Commands for Logistic Regression 31011.9 Exercise 31011.9.1 Short Answer Questions 31011.9.2 Multiple Choice Questions 31111.9.3 Assignment 31211.10 Case Study on Logistic Regression 31312 Application of Factor Analysis 31912.1 Introduction 31912.2 Terminologies Used in Factor Analysis 32012.2.1 Principal Component Analysis 32012.2.2 Eigenvalue 32012.2.3 Kaiser Criterion 32112.2.4 The Scree Test 32112.2.5 Communality 32112.2.6 Factor Loading 32212.2.7 Varimax Rotation 32212.3 Assumptions in Factor Analysis 32212.4 Steps in Factor Analysis 32312.5 Application of Factor Analysis 32312.6 Factor Analysis with Spss 32412.6.1 Computation in Factor Analysis Using SPSS 32612.7 Summary of the Spss Commands for Factor Analysis 33612.8 Exercise 33612.8.1 Short Answer Questions 33612.8.2 Multiple Choice Questions 33712.8.3 Assignment 33812.9 Case Study on Factor Analysis 339Appendix 346Bibliography 360Index 368