Title Page	5
	Copyright Page	6
	Contents	9
	Preface	17
	About the Companion Website	20
	Chapter 1 Introduction to Data Types and SPSS Operations	23
	1.1 INTRODUCTION	23
	1.2 TYPES OF DATA	24
	1.2.1 Qualitative Data	24
	1.2.2 Quantitative Data	25
	1.3 IMPORTANT DEFINITIONS	26
	1.3.1 Variable	26
	1.4 DATA CLEANING	26
	1.5 DETECTION OF ERRORS	27
	1.5.1 Using Frequencies	27
	1.5.2 Using Mean and Standard Deviation	27
	1.5.3 Logic Checks	27
	1.5.4 Outlier Detection	27
	1.6 HOW TO START SPSS?	28
	1.6.1 Preparing Data File	29
	1.7 EXERCISE	32
	1.7.1 Short Answer Questions	32
	1.7.2 Multiple Choice Questions	33
	Chapter 2 Descriptive Profile	36
	2.1 INTRODUCTION	36
	2.2 EXPLANATION OF VARIOUS DESCRIPTIVE STATISTICS	38
	2.2.1 Mean	38
	2.2.2 Variance	38
	2.2.3 Standard Error of Mean	39
	2.2.4 Skewness	39
	2.2.5 Kurtosis	40
	2.2.6 Percentiles	41
	2.3 APPLICATION OF DESCRIPTIVE STATISTICS	41
	2.3.1 Testing Normality of Data and Identifying Outliers	42
	2.4 COMPUTATION OF DESCRIPTIVE STATISTICS USING SPSS	47
	2.4.1 Preparation of Data File	47
	2.4.2 Defining Variables	48
	2.4.3 Entering Data	48
	2.4.4 SPSS Commands	48
	2.5 INTERPRETATIONS OF THE RESULTS	51
	2.6 DEVELOPING PROFILE CHART	53
	2.7 SUMMARY OF SPSS COMMANDS	55
	2.8 EXERCISE	55
	2.8.1 Short Answer Questions	55
	2.8.2 Multiple Choice Questions	56
	2.9 CASE STUDY ON DESCRIPTIVE ANALYSIS	58
	Chapter 3 Correlation Coefficient and Partial Correlation	63
	3.1 INTRODUCTION	63
	3.2 CORRELATION MATRIX AND PARTIAL CORRELATION	65
	3.2.1 Product Moment Correlation Coefficient	65
	3.2.2 Partial Correlation	67
	3.3 APPLICATION OF CORRELATION MATRIX AND PARTIAL CORRELATION	68
	3.4 CORRELATION MATRIX WITH SPSS	68
	3.4.1 Computation in Correlation Matrix	68
	3.4.2 Interpretations of Findings	73
	3.5 PARTIAL CORRELATION WITH SPSS	73
	3.5.1 Computation of Partial Correlations	74
	3.5.2 Interpretation of Partial Correlation	77
	3.6 SUMMARY OF THE SPSS COMMANDS	78
	3.6.1 For Computing Correlation Matrix	78
	3.6.2 For Computing Partial Correlations	79
	3.7 EXERCISE	79
	3.7.1 Short Answer Questions	79
	3.7.2 Multiple Choice Questions	79
	3.7.3 Assignment	82
	3.8 CASE STUDY ON CORRELATION	82
	Chapter 4 Comparing Means	87
	4.1 INTRODUCTION	87
	4.2 ONE-SAMPLE t-TEST	88
	4.2.1 Application of One-Sample t-Test	89
	4.3 TWO-SAMPLE t-TEST FOR UNRELATED GROUPS	89
	4.3.1 Assumptions While Using t-Test	89
	4.3.2 Case I: Two-Tailed Test	90
	4.3.3 Case II: Right Tailed Test	90
	4.3.4 Case III: Left Tailed Test	91
	4.3.5 Application of Two-Sample t-Test	92
	4.4 PAIRED t-TEST FOR RELATED GROUPS	92
	4.4.1 Case I: Two-Tailed Test	93
	4.4.2 Case II: Right Tailed Test	93
	4.4.3 Case III: Left Tailed Test	94
	4.4.4 Application of Paired t-Test	95
	4.5 ONE-SAMPLE t-TEST WITH SPSS	95
	4.5.1 Computation in t-Test for Single Group	96
	4.5.2 Interpretation of Findings	99
	4.6 TWO-SAMPLE t-TEST FOR INDEPENDENT GROUPS WITH SPSS	100
	4.6.1 Computation in Two-Sample t-Test	101
	4.6.2 Interpretation of Findings	105
	4.7 PAIRED t-TEST FOR RELATED GROUPS WITH SPSS	107
	4.7.1 Computation in Paired t-Test	108
	4.7.2 Interpretation of Findings	111
	4.8 SUMMARY OF SPSS COMMANDS FOR t-TESTS	112
	4.8.1 One-Sample t-Test	112
	4.8.2 Two-Sample t-Test for Independent Groups	112
	4.8.3 Paired t-Test	113
	4.9 EXERCISE	113
	4.9.1 Short Answer Questions	113
	4.9.2 Multiple Choice Questions	113
	4.9.3 Assignment	115
	4.10 CASE STUDY	116
	Chapter 5 Independent Measures Anova	122
	5.1 INTRODUCTION	123
	5.2 ONE-WAY ANALYSIS OF VARIANCE	123
	5.2.1 One-Way ANOVA Model	124
	5.2.2 Post Hoc Test	124
	5.2.3 Application of One-Way ANOVA	125
	5.3 ONE-WAY ANOVA WITH SPSS (EQUAL SAMPLE SIZE)	125
	5.3.1 Computation in One-Way ANOVA (Equal Sample Size)	126
	5.3.2 Interpretation of Findings	129
	5.4 ONE-WAY ANOVA WITH SPSS (UNEQUAL SAMPLE SIZE)	132
	5.4.1 Computation in One-Way ANOVA (Unequal Sample Size)	133
	5.4.2 Interpretation of Findings	136
	5.5 TWO-WAY ANALYSIS OF VARIANCE	137
	5.5.1 Assumptions in Two-Way Analysis of Variance	138
	5.5.2 Hypotheses in Two-Way ANOVA	138
	5.5.3 Factors	139
	5.5.4 Treatment Groups	139
	5.5.5 Main Effect	139
	5.5.6 Interaction Effect	139
	5.5.7 Within-Groups Variation	139
	5.5.8 F-Statistic	139
	5.5.9 Two-Way ANOVA Table	140
	5.5.10 Interpretation	140
	5.5.11 Application of Two-Way Analysis of Variance	140
	5.6 TWO-WAY ANOVA USING SPSS	141
	5.6.1 Computation in Two-Way ANOVA	143
	5.6.2 Interpretation of Findings	148
	5.7 SUMMARY OF THE SPSS COMMANDS	159
	5.7.1 One-Way ANOVA	159
	5.7.2 Two-Way ANOVA	160
	5.8 EXERCISE	160
	5.8.1 Short Answer Questions	160
	5.8.2 Multiple Choice Questions	161
	5.8.3 Assignment	164
	5.9 CASE STUDY ON ONE-WAY ANOVA DESIGN	165
	5.10 CASE STUDY ON TWO-WAY ANOVA	169
	Chapter 6 Repeated Measures Anova	175
	6.1 INTRODUCTION	175
	6.2 ONE-WAY REPEATED MEASURES ANOVA	176
	6.2.1 Assumptions in One-Way Repeated Measures ANOVA	177
	6.2.2 Application in Sports Research	177
	6.2.3 Steps in Solving One-Way Repeated Measures ANOVA	178
	6.3 ONE-WAY REPEATED MEASURES ANOVA USING SPSS	179
	6.3.1 Computation in the One-Way Repeated Measures ANOVA	179
	6.3.2 Interpretation of Findings	183
	6.3.3 Findings of the Study	187
	6.3.4 Inference	188
	6.4 TWO-WAY REPEATED MEASURES ANOVA	188
	6.4.1 Assumptions in Two-Way Repeated Measures ANOVA	188
	6.4.2 Application in Sports Research	189
	6.4.3 Steps in Solving Two-Way Repeated Measures ANOVA	189
	6.5 TWO-WAY REPEATED MEASURES ANOVA USING SPSS	190
	6.5.1 Computation in Two-Way Repeated Measures ANOVA	192
	6.5.2 Interpretation of Findings	195
	6.5.3 Findings of the Study	203
	6.5.4 Inference	203
	6.6 SUMMARY OF THE SPSS COMMANDS FOR ONE-WAY REPEATED MEASURES ANOVA	204
	6.7 SUMMARY OF THE SPSS COMMANDS FOR TWO-WAY REPEATED MEASURES ANOVA	204
	6.8 EXERCISE	205
	6.8.1 Short Answer Questions	205
	6.8.2 Multiple Choice Questions	205
	6.8.3 Assignment	207
	6.9 CASE STUDY ON REPEATED MEASURES DESIGN	208
	Chapter 7 Analysis of Covariance	212
	7.1 INTRODUCTION	212
	7.2 CONCEPTUAL FRAMEWORK OF ANALYSIS OF COVARIANCE	213
	7.3 APPLICATION OF ANCOVA	214
	7.4 ANCOVA WITH SPSS	215
	7.4.1 Computation in ANCOVA	216
	7.5 SUMMARY OF THE SPSS COMMANDS	223
	7.6 EXERCISE	224
	7.6.1 Short Answer Questions	224
	7.6.2 Multiple Choice Questions	224
	7.6.3 Assignment	225
	7.7 CASE STUDY ON ANCOVA DESIGN	226
	Chapter 8 Nonparametric Tests in Sports Research	231
	8.1 INTRODUCTION	231
	8.2 CHI-SQUARE TEST	233
	8.2.1 Testing Goodness of Fit	233
	8.2.2 Yates’ Correction	234
	8.2.3 Contingency Coefficient	234
	8.3 GOODNESS OF FIT WITH SPSS	234
	8.3.1 Computation in Goodness of Fit	235
	8.3.2 Interpretation of Findings	238
	8.4 TESTING INDEPENDENCE OF TWO ATTRIBUTES	238
	8.4.1 Interpretation	240
	8.5 TESTING ASSOCIATION WITH SPSS	241
	8.5.1 Computation in Chi-Square	241
	8.5.2 Interpretation of Findings	245
	8.6 MANN–WHITNEY U TEST: COMPARING TWO INDEPENDENT SAMPLES	246
	8.6.1 Computation in Mann–Whitney U Statistic Using SPSS	246
	8.6.2 Interpretation of Findings	248
	8.7 WILCOXON SIGNED-RANK TEST: FOR COMPARING TWO RELATED GROUPS	249
	8.7.1 Computation in Wilcoxon Signed-Rank Test Using SPSS	250
	8.7.2 Interpretation of Findings	252
	8.8 KRUSKAL–WALLIS TEST	253
	8.8.1 Computation in Kruskal–Wallis Test Using SPSS	254
	8.8.2 Interpretation of Findings	256
	8.9 FRIEDMAN TEST	256
	8.9.1 Computation in Friedman Test Using SPSS	257
	8.9.2 Interpretation of Findings	259
	8.10 SUMMARY OF THE SPSS COMMANDS	259
	8.10.1 Computing Chi-Square Statistic (for Testing Goodness of Fit)	259
	8.10.2 Computing Chi-Square Statistic (for Testing Independence)	260
	8.10.3 Computation in Mann–Whitney U Test	260
	8.10.4 Computation in Wilcoxon Signed-Rank Test	261
	8.10.5 Computation in Kruskal–Wallis Test	261
	8.10.6 Computation in Friedman Test	261
	8.11 EXERCISE	262
	8.11.1 Short Answer Questions	262
	8.11.2 Multiple Choice Questions	263
	8.11.3 Assignment	265
	8.12 CASE STUDY ON TESTING INDEPENDENCE OF ATTRIBUTES	265
	Chapter 9 Regression Analysis and Multiple Correlations	268
	9.1 INTRODUCTION	268
	9.2 UNDERSTANDING REGRESSION EQUATION	269
	9.2.1 Methods of Regression Analysis	269
	9.2.2 Multiple Correlation	270
	9.3 APPLICATION OF REGRESSION ANALYSIS	270
	9.4 MULTIPLE REGRESSION ANALYSIS WITH SPSS	271
	9.4.1 Computation in Regression Analysis	271
	9.4.2 Interpretation of Findings	276
	9.5 SUMMARY OF SPSS COMMANDS FOR REGRESSION ANALYSIS	281
	9.6 Exercise	281
	9.6.1 Short Answer Questions	281
	9.6.2 Multiple Choice Questions	282
	9.6.3 Assignment	283
	9.7 CASE STUDY ON REGRESSION ANALYSIS	285
	Chapter 10 Application of Discriminant Function Analysis	289
	10.1 INTRODUCTION	290
	10.2 BASICS OF DISCRIMINANT FUNCTION ANALYSIS	290
	10.2.1 Discriminating Variables	290
	10.2.2 Dependent Variable	290
	10.2.3 Discriminant Function	290
	10.2.4 Classification Matrix	291
	10.2.5 Stepwise Method of Discriminant Analysis	291
	10.2.6 Power of Discriminating Variable	291
	10.2.7 Canonical Correlation	291
	10.2.8 Wilks’ Lambda	292
	10.3 ASSUMPTIONS IN DISCRIMINANT ANALYSIS	292
	10.4 WHY TO USE DISCRIMINANT ANALYSIS	292
	10.5 STEPS IN DISCRIMINANT ANALYSIS	293
	10.6 APPLICATION OF DISCRIMINANT FUNCTION ANALYSIS	294
	10.7 DISCRIMINANT ANALYSIS USING SPSS	296
	10.7.1 Computation in Discriminant Analysis	296
	10.7.2 Interpretation of Findings	301
	10.8 SUMMARY OF THE SPSS COMMANDS FOR DISCRIMINANT ANALYSIS	306
	10.9 EXERCISE	306
	10.9.1 Short Answer Questions	306
	10.9.2 Multiple Choice Questions	307
	10.9.3 Assignment	308
	10.10 CASE STUDY ON DISCRIMINANT ANALYSIS	310
	Chapter 11 Logistic Regression for Developing Logit Model in Sport	315
	11.1 INTRODUCTION	315
	11.2 UNDERSTANDING LOGISTIC REGRESSION	316
	11.3 APPLICATION OF LOGISTIC REGRESSION IN SPORTS RESEARCH	317
	11.4 ASSUMPTIONS IN LOGISTIC REGRESSION	319
	11.5 STEPS IN DEVELOPING LOGISTIC MODEL	319
	11.6 LOGISTIC ANALYSIS USING SPSS	319
	11.6.1 Block 0	321
	11.6.2 Block 1	321
	11.6.3 Computation in Logistic Regression with SPSS	321
	11.7 INTERPRETATION OF FINDINGS	326
	11.7.1 Case Processing and Coding Summary	326
	11.7.2 Analyzing Logistic models	327
	11.8 SUMMARY OF THE SPSS COMMANDS FOR LOGISTIC REGRESSION	332
	11.9 EXERCISE	332
	11.9.1 Short Answer Questions	332
	11.9.2 Multiple Choice Questions	333
	11.9.3 Assignment	334
	11.10 CASE STUDY ON LOGISTIC REGRESSION	335
	Chapter 12 Application of Factor Analysis	341
	12.1 INTRODUCTION	341
	12.2 Terminologies Used in Factor Analysis	342
	12.2.1 Principal Component Analysis	342
	12.2.2 Eigenvalue	342
	12.2.3 Kaiser Criterion	343
	12.2.4 The Scree Test	343
	12.2.5 Communality	343
	12.2.6 Factor Loading	344
	12.2.7 Varimax Rotation	344
	12.3 Assumptions in Factor Analysis	344
	12.4 STEPS IN FACTOR ANALYSIS	345
	12.5 APPLICATION OF FACTOR ANALYSIS	345
	12.6 Factor Analysis with SPSS	346
	12.6.1 Computation in Factor Analysis Using SPSS	348
	12.7 SUMMARY OF THE SPSS COMMANDS FOR FACTOR ANALYSIS	358
	12.8 Exercise	358
	12.8.1 Short Answer Questions	358
	12.8.2 Multiple Choice Questions	359
	12.8.3 Assignment	360
	12.9 Case Study on Factor Analysis	361
	Appendix	368
	Bibliography	382
	Index	390
	EULA	394