Statistics for Exercise Science and Health with Microsoft Office Excel

J. P. Verma, PhD, is Professor of Statistics and Director of the Center for Advanced Studies at Lakshmibai National Institute of Physical Education in Gwalior, India. Professor Verma is an active researcher in sports modeling and data analysis and has conducted many workshops on research methodology, research designs, multivariate analysis, statistical modeling, and data analysis for students of management, physical education, social science, and economics.

• Preface xxi1 Scope of Statistics in Exercise Science and Health 11.1 Introduction, 11.2 Understanding Statistics, 21.3 What Statistics Does?, 31.4 Statistical Processes, 41.5 Need for Statistics, 51.6 Statistics in Exercise Science and Health, 81.7 Computing with Excel, 92 Understanding the Nature of Data 192.1 Introduction, 192.2 Important Terminologies, 202.3 Measurement of Data, 222.4 Parametric and Nonparametric Statistics, 242.5 Frequency Distribution, 252.6 Summation Notation, 282.7 Measures of Central Tendency, 342.8 Comparison of the Mean, Median, and Mode, 462.9 Measures of Variability, 532.10 Standard Error, 722.11 Coefficient of Variation, 722.12 Absolute and Relative Variability, 742.13 Box-And-Whisker Plot, 792.14 Skewness, 812.15 Percentiles, 822.16 Computing with Excel, 863 Working with Graphs 1013.1 Introduction, 1013.2 Guidelines for Constructing a Graph, 1023.3 Bar Diagram, 1043.4 Histogram, 1053.5 Frequency Polygon, 1073.6 Frequency Curve, 1073.7 Cumulative Frequency Curve, 1083.8 Ogive, 1103.9 Pie Diagram, 1113.10 Stem and Leaf Plot, 1133.11 Computing with Excel, 1174 Probability and its Application 1304.1 Introduction, 1304.2 Application of Probability, 1314.3 Set Theory, 1324.4 Terminologies Used in Probability, 1364.5 Basic Definitions of Probability, 1424.6 Some Results on Probability, 1454.7 Computing Probability, 1454.8 Types of Probability, 1514.9 Theorems of Probability, 1524.10 Computing with Excel, 1625 Statistical Distributions and their Application 1765.1 Introduction, 1765.2 Terminologies used in Statistical Distribution, 1775.3 Discrete Distribution, 1825.4 Binomial Distribution, 1835.5 Poisson Distribution, 1895.6 Continuous Distribution, 1945.7 Normal Distribution, 1955.8 Standard Score, 1985.9 Normal Approximation to the Binomial Distribution, 1995.10 Testing Normality of the Data, 2005.11 The Central Limit Theorem, 2045.12 Solving Problems Based on Normal Distribution, 2045.13 Uses of Normal Distribution, 2165.14 Computing with Excel, 2176 Sampling and Sampling Distribution 2346.1 Introduction, 2346.2 Population and Sample, 2356.3 Parameter and Statistics, 2356.4 Sampling Frame, 2366.5 Sampling, 2366.6 Census, 2386.7 Probability and Nonprobability Sampling, 2386.8 Probability Sampling, 2396.9 Nonprobability Sampling, 2466.10 When to Use Probability Sampling, 2496.11 When to Use Nonprobability Sampling, 2506.12 Characteristics of a Good Sample, 2506.13 Sources of Data, 2516.14 Methods of Data Collection, 2526.15 Biases in Data Collection, 2546.16 Sampling Error, 2556.17 Nonsampling Errors, 2556.18 Sampling Distribution, 2556.19 Criteria in Deciding Sample Size, 2626.20 Computing with Excel, 2667 Statistical Inference for Decision-Making in Exercise Science and Health 2777.1 Introduction, 2777.2 Theory of Estimation, 2787.3 Point Estimation, 2787.4 Characteristics of a Good Estimator, 2797.5 The t-Distribution, 2807.6 Interval Estimation, 2817.7 Testing of Hypothesis, 2957.8 Types of Hypothesis, 2967.9 Test Statistic, 2977.10 Concept used in Hypothesis Testing, 2987.11 Type I and Type II Errors, 2997.12 Level of Significance, 3007.13 Power of the Test, 3017.14 Rejection Region and Critical Value, 3017.15 p-Value, 3027.16 One-Tailed and Two-Tailed Tests, 3037.17 Degrees of Freedom, 3057.18 Strategy in Selecting the Test Statistic, 3067.19 Steps in Hypothesis Testing, 3077.20 One-Sample Testing, 3127.21 Two-Sample Testing, 3247.22 Test of Significance about Two Population Proportions, 3387.23 Test of Significance about Two Population Variances, 3417.24 Computing with Excel, 3468 Analysis of Variance and Designing Research Experiments 3758.1 Introduction, 3758.2 Understanding Analysis of Variance, 3768.3 Design of Experiment, 3788.4 One-way Analysis of Variance, 3798.5 Completely Randomized Design, 3848.6 Two-way Analysis of Variance (N Observations Per Cell), 3918.7 Two-way Analysis of Variance (One Observation Per Cell), 3978.8 Randomized Block Design, 4018.9 Factorial Design, 4078.10 Analysis of Covariance, 4148.11 Computing with Excel, 4289 Understanding Relationships and Developing Regression Models 4619.1 Introduction, 4619.2 Types of Relationship, 4629.3 Correlation Coefficient, 4639.4 Partial Correlation, 4769.5 Multiple Correlation, 4809.6 Suppression Variable, 4839.7 Regression Analysis, 4859.8 The Multiple Regression Model, 5109.9 Different Ways of Testing a Regression Model, 5159.10 Law of Diminishing Returns, 5239.11 Different Approaches in Developing Multiple Regression Models, 5249.12 Computing with Excel, 52810 Statistical Tests for Nonparametric Data 55610.1 Introduction, 55610.2 Merits and Demerits of Nonparametric Tests, 55710.3 Chi-Square Test, 55710.4 Runs Test, 57110.5 Mann–Whitney U-Test for Two Samples, 57710.6 Wilcoxon Matched-Pairs Signed-Ranks Test, 58410.7 Kruskal–Wallis Test (One-Way ANOVA for Nonparametric Data), 58910.8 The Friedman Test, 59310.9 Computing with Excel, 59911 Measuring Associations in Nonparametric Data 61511.1 Introduction, 61511.2 Rank Correlation (Measure of Association Between Ranked Data), 61611.3 Bi-Serial Correlation (Measure of Association Between a Dichotomous and a Continuous Variable), 62211.4 Point Bi-Serial Correlation (Measure of Correlation Between a True Dichotomous Variable and a Continuous Variable), 62411.5 Tetrachoric Correlation (Measure of Association Between Dichotomous Variables), 62911.6 Phi Coefficient (Measure of Association Between Naturally Dichotomous Variables), 63611.7 Contingency Coefficient (Measure of Association Between Categorical Variables), 64011.8 Computing with Excel, 64612 Developing Norms for Assessing Performance 65712.1 Introduction, 65712.2 Percentiles, 65812.3 Z-Scale, 66312.4 T-Scale, 66412.5 Stanine Scale, 66412.6 Composite Scale Based on Z-Score, 66612.7 Scaling of Ratings in Terms of the Normal Curve, 67112.8 Developing Norms Based on Difficulty Ratings, 67412.9 Computing with Excel, 677Appendix: Statistical Tables 688Table A.1 Trigonometric Function, 688Table A.2 Binomial Probability Distribution, 691Table A.3 Poisson Probability Distribution, 695Table A.4 The Normal Curve Area Between the Mean and a Given z Value, 700Table A.5 Ordinates at Different Values of z-Score in the Standard Normal Distribution, 701Table A.6 Standard Scores (or Deviates) and Ordinates Corresponding to Divisions of the Area under the Normal Curve into a Larger Proportion (B) and a Smaller Proportion (C), 704Table A.7 Critical Values of “t”, 707Table A.8 Critical Values of the Correlation Coefficient, 708Table A.9 F-Table: Critical Values = 0.05, 709Table A.10 F-Table: Critical Values = 0.01, 710Table A.11 The Chi-square Table, 711Table A.12 Critical Values for Number of Runs R, 712Table A.13 Critical Values for the Mann–Whitney U-Test, 713Table A.14 Critical Values of T for the Wilcoxon Matched-pairs Signed-ranks Test (Small Samples), 713Table A.15 Critical Values of Studentized Range Distribution(q) for Familywise = .05, 714Index 717