Description

Book Synopsis

This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis.

Statistics for Exercise Science and Health with Microsoft Office Excel:

  • Aids readers in analyzing their own data using the presented statistical techniques combined with Excel
  • Features comprehensive coverage of hypothesis testing and regression models tofacilitate modeling in sports science
  • Utilizes Excel to enhance reader competency in data analysis and experimental designs
  • Includes coverage of both binomial and poison distributions with applications in exercise science and health
  • Provides solved examples and plentiful practice exercises throughout in addition to case studies to illustrate the discussed analytical techniques
  • Contains all needed definitions and formulas to aid readers in understanding different statistical con

    Table of Contents

    Preface xxi

    1 Scope of Statistics in Exercise Science and Health 1

    1.1 Introduction, 1

    1.2 Understanding Statistics, 2

    1.3 What Statistics Does?, 3

    1.4 Statistical Processes, 4

    1.5 Need for Statistics, 5

    1.6 Statistics in Exercise Science and Health, 8

    1.7 Computing with Excel, 9

    2 Understanding the Nature of Data 19

    2.1 Introduction, 19

    2.2 Important Terminologies, 20

    2.3 Measurement of Data, 22

    2.4 Parametric and Nonparametric Statistics, 24

    2.5 Frequency Distribution, 25

    2.6 Summation Notation, 28

    2.7 Measures of Central Tendency, 34

    2.8 Comparison of the Mean, Median, and Mode, 46

    2.9 Measures of Variability, 53

    2.10 Standard Error, 72

    2.11 Coefficient of Variation, 72

    2.12 Absolute and Relative Variability, 74

    2.13 Box-And-Whisker Plot, 79

    2.14 Skewness, 81

    2.15 Percentiles, 82

    2.16 Computing with Excel, 86

    3 Working with Graphs 101

    3.1 Introduction, 101

    3.2 Guidelines for Constructing a Graph, 102

    3.3 Bar Diagram, 104

    3.4 Histogram, 105

    3.5 Frequency Polygon, 107

    3.6 Frequency Curve, 107

    3.7 Cumulative Frequency Curve, 108

    3.8 Ogive, 110

    3.9 Pie Diagram, 111

    3.10 Stem and Leaf Plot, 113

    3.11 Computing with Excel, 117

    4 Probability and its Application 130

    4.1 Introduction, 130

    4.2 Application of Probability, 131

    4.3 Set Theory, 132

    4.4 Terminologies Used in Probability, 136

    4.5 Basic Definitions of Probability, 142

    4.6 Some Results on Probability, 145

    4.7 Computing Probability, 145

    4.8 Types of Probability, 151

    4.9 Theorems of Probability, 152

    4.10 Computing with Excel, 162

    5 Statistical Distributions and their Application 176

    5.1 Introduction, 176

    5.2 Terminologies used in Statistical Distribution, 177

    5.3 Discrete Distribution, 182

    5.4 Binomial Distribution, 183

    5.5 Poisson Distribution, 189

    5.6 Continuous Distribution, 194

    5.7 Normal Distribution, 195

    5.8 Standard Score, 198

    5.9 Normal Approximation to the Binomial Distribution, 199

    5.10 Testing Normality of the Data, 200

    5.11 The Central Limit Theorem, 204

    5.12 Solving Problems Based on Normal Distribution, 204

    5.13 Uses of Normal Distribution, 216

    5.14 Computing with Excel, 217

    6 Sampling and Sampling Distribution 234

    6.1 Introduction, 234

    6.2 Population and Sample, 235

    6.3 Parameter and Statistics, 235

    6.4 Sampling Frame, 236

    6.5 Sampling, 236

    6.6 Census, 238

    6.7 Probability and Nonprobability Sampling, 238

    6.8 Probability Sampling, 239

    6.9 Nonprobability Sampling, 246

    6.10 When to Use Probability Sampling, 249

    6.11 When to Use Nonprobability Sampling, 250

    6.12 Characteristics of a Good Sample, 250

    6.13 Sources of Data, 251

    6.14 Methods of Data Collection, 252

    6.15 Biases in Data Collection, 254

    6.16 Sampling Error, 255

    6.17 Nonsampling Errors, 255

    6.18 Sampling Distribution, 255

    6.19 Criteria in Deciding Sample Size, 262

    6.20 Computing with Excel, 266

    7 Statistical Inference for Decision-Making in Exercise Science and Health 277

    7.1 Introduction, 277

    7.2 Theory of Estimation, 278

    7.3 Point Estimation, 278

    7.4 Characteristics of a Good Estimator, 279

    7.5 The t-Distribution, 280

    7.6 Interval Estimation, 281

    7.7 Testing of Hypothesis, 295

    7.8 Types of Hypothesis, 296

    7.9 Test Statistic, 297

    7.10 Concept used in Hypothesis Testing, 298

    7.11 Type I and Type II Errors, 299

    7.12 Level of Significance, 300

    7.13 Power of the Test, 301

    7.14 Rejection Region and Critical Value, 301

    7.15 p-Value, 302

    7.16 One-Tailed and Two-Tailed Tests, 303

    7.17 Degrees of Freedom, 305

    7.18 Strategy in Selecting the Test Statistic, 306

    7.19 Steps in Hypothesis Testing, 307

    7.20 One-Sample Testing, 312

    7.21 Two-Sample Testing, 324

    7.22 Test of Significance about Two Population Proportions, 338

    7.23 Test of Significance about Two Population Variances, 341

    7.24 Computing with Excel, 346

    8 Analysis of Variance and Designing Research Experiments 375

    8.1 Introduction, 375

    8.2 Understanding Analysis of Variance, 376

    8.3 Design of Experiment, 378

    8.4 One-way Analysis of Variance, 379

    8.5 Completely Randomized Design, 384

    8.6 Two-way Analysis of Variance (N Observations Per Cell), 391

    8.7 Two-way Analysis of Variance (One Observation Per Cell), 397

    8.8 Randomized Block Design, 401

    8.9 Factorial Design, 407

    8.10 Analysis of Covariance, 414

    8.11 Computing with Excel, 428

    9 Understanding Relationships and Developing Regression Models 461

    9.1 Introduction, 461

    9.2 Types of Relationship, 462

    9.3 Correlation Coefficient, 463

    9.4 Partial Correlation, 476

    9.5 Multiple Correlation, 480

    9.6 Suppression Variable, 483

    9.7 Regression Analysis, 485

    9.8 The Multiple Regression Model, 510

    9.9 Different Ways of Testing a Regression Model, 515

    9.10 Law of Diminishing Returns, 523

    9.11 Different Approaches in Developing Multiple Regression Models, 524

    9.12 Computing with Excel, 528

    10 Statistical Tests for Nonparametric Data 556

    10.1 Introduction, 556

    10.2 Merits and Demerits of Nonparametric Tests, 557

    10.3 Chi-Square Test, 557

    10.4 Runs Test, 571

    10.5 Mann–Whitney U-Test for Two Samples, 577

    10.6 Wilcoxon Matched-Pairs Signed-Ranks Test, 584

    10.7 Kruskal–Wallis Test (One-Way ANOVA for Nonparametric Data), 589

    10.8 The Friedman Test, 593

    10.9 Computing with Excel, 599

    11 Measuring Associations in Nonparametric Data 615

    11.1 Introduction, 615

    11.2 Rank Correlation (Measure of Association Between Ranked Data), 616

    11.3 Bi-Serial Correlation (Measure of Association Between a Dichotomous and a Continuous Variable), 622

    11.4 Point Bi-Serial Correlation (Measure of Correlation Between a True Dichotomous Variable and a Continuous Variable), 624

    11.5 Tetrachoric Correlation (Measure of Association Between Dichotomous Variables), 629

    11.6 Phi Coefficient (Measure of Association Between Naturally Dichotomous Variables), 636

    11.7 Contingency Coefficient (Measure of Association Between Categorical Variables), 640

    11.8 Computing with Excel, 646

    12 Developing Norms for Assessing Performance 657

    12.1 Introduction, 657

    12.2 Percentiles, 658

    12.3 Z-Scale, 663

    12.4 T-Scale, 664

    12.5 Stanine Scale, 664

    12.6 Composite Scale Based on Z-Score, 666

    12.7 Scaling of Ratings in Terms of the Normal Curve, 671

    12.8 Developing Norms Based on Difficulty Ratings, 674

    12.9 Computing with Excel, 677

    Appendix: Statistical Tables 688

    Table A.1 Trigonometric Function, 688

    Table A.2 Binomial Probability Distribution, 691

    Table A.3 Poisson Probability Distribution, 695

    Table A.4 The Normal Curve Area Between the Mean and a Given z Value, 700

    Table A.5 Ordinates at Different Values of z-Score in the Standard Normal Distribution, 701

    Table 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), 704

    Table A.7 Critical Values of “t”, 707

    Table A.8 Critical Values of the Correlation Coefficient, 708

    Table A.9 F-Table: Critical Values = 0.05, 709

    Table A.10 F-Table: Critical Values = 0.01, 710

    Table A.11 The Chi-square Table, 711

    Table A.12 Critical Values for Number of Runs R, 712

    Table A.13 Critical Values for the Mann–Whitney U-Test, 713

    Table A.14 Critical Values of T for the Wilcoxon Matched-pairs Signed-ranks Test (Small Samples), 713

    Table A.15 Critical Values of Studentized Range Distribution(q) for Familywise = .05, 714

    Index 717

Statistics for Exercise Science and Health with

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      Publisher: John Wiley & Sons Inc
      Publication Date: 08/08/2014
      ISBN13: 9781118855218, 978-1118855218
      ISBN10: 1118855213

      Description

      Book Synopsis

      This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis.

      Statistics for Exercise Science and Health with Microsoft Office Excel:

      • Aids readers in analyzing their own data using the presented statistical techniques combined with Excel
      • Features comprehensive coverage of hypothesis testing and regression models tofacilitate modeling in sports science
      • Utilizes Excel to enhance reader competency in data analysis and experimental designs
      • Includes coverage of both binomial and poison distributions with applications in exercise science and health
      • Provides solved examples and plentiful practice exercises throughout in addition to case studies to illustrate the discussed analytical techniques
      • Contains all needed definitions and formulas to aid readers in understanding different statistical con

        Table of Contents

        Preface xxi

        1 Scope of Statistics in Exercise Science and Health 1

        1.1 Introduction, 1

        1.2 Understanding Statistics, 2

        1.3 What Statistics Does?, 3

        1.4 Statistical Processes, 4

        1.5 Need for Statistics, 5

        1.6 Statistics in Exercise Science and Health, 8

        1.7 Computing with Excel, 9

        2 Understanding the Nature of Data 19

        2.1 Introduction, 19

        2.2 Important Terminologies, 20

        2.3 Measurement of Data, 22

        2.4 Parametric and Nonparametric Statistics, 24

        2.5 Frequency Distribution, 25

        2.6 Summation Notation, 28

        2.7 Measures of Central Tendency, 34

        2.8 Comparison of the Mean, Median, and Mode, 46

        2.9 Measures of Variability, 53

        2.10 Standard Error, 72

        2.11 Coefficient of Variation, 72

        2.12 Absolute and Relative Variability, 74

        2.13 Box-And-Whisker Plot, 79

        2.14 Skewness, 81

        2.15 Percentiles, 82

        2.16 Computing with Excel, 86

        3 Working with Graphs 101

        3.1 Introduction, 101

        3.2 Guidelines for Constructing a Graph, 102

        3.3 Bar Diagram, 104

        3.4 Histogram, 105

        3.5 Frequency Polygon, 107

        3.6 Frequency Curve, 107

        3.7 Cumulative Frequency Curve, 108

        3.8 Ogive, 110

        3.9 Pie Diagram, 111

        3.10 Stem and Leaf Plot, 113

        3.11 Computing with Excel, 117

        4 Probability and its Application 130

        4.1 Introduction, 130

        4.2 Application of Probability, 131

        4.3 Set Theory, 132

        4.4 Terminologies Used in Probability, 136

        4.5 Basic Definitions of Probability, 142

        4.6 Some Results on Probability, 145

        4.7 Computing Probability, 145

        4.8 Types of Probability, 151

        4.9 Theorems of Probability, 152

        4.10 Computing with Excel, 162

        5 Statistical Distributions and their Application 176

        5.1 Introduction, 176

        5.2 Terminologies used in Statistical Distribution, 177

        5.3 Discrete Distribution, 182

        5.4 Binomial Distribution, 183

        5.5 Poisson Distribution, 189

        5.6 Continuous Distribution, 194

        5.7 Normal Distribution, 195

        5.8 Standard Score, 198

        5.9 Normal Approximation to the Binomial Distribution, 199

        5.10 Testing Normality of the Data, 200

        5.11 The Central Limit Theorem, 204

        5.12 Solving Problems Based on Normal Distribution, 204

        5.13 Uses of Normal Distribution, 216

        5.14 Computing with Excel, 217

        6 Sampling and Sampling Distribution 234

        6.1 Introduction, 234

        6.2 Population and Sample, 235

        6.3 Parameter and Statistics, 235

        6.4 Sampling Frame, 236

        6.5 Sampling, 236

        6.6 Census, 238

        6.7 Probability and Nonprobability Sampling, 238

        6.8 Probability Sampling, 239

        6.9 Nonprobability Sampling, 246

        6.10 When to Use Probability Sampling, 249

        6.11 When to Use Nonprobability Sampling, 250

        6.12 Characteristics of a Good Sample, 250

        6.13 Sources of Data, 251

        6.14 Methods of Data Collection, 252

        6.15 Biases in Data Collection, 254

        6.16 Sampling Error, 255

        6.17 Nonsampling Errors, 255

        6.18 Sampling Distribution, 255

        6.19 Criteria in Deciding Sample Size, 262

        6.20 Computing with Excel, 266

        7 Statistical Inference for Decision-Making in Exercise Science and Health 277

        7.1 Introduction, 277

        7.2 Theory of Estimation, 278

        7.3 Point Estimation, 278

        7.4 Characteristics of a Good Estimator, 279

        7.5 The t-Distribution, 280

        7.6 Interval Estimation, 281

        7.7 Testing of Hypothesis, 295

        7.8 Types of Hypothesis, 296

        7.9 Test Statistic, 297

        7.10 Concept used in Hypothesis Testing, 298

        7.11 Type I and Type II Errors, 299

        7.12 Level of Significance, 300

        7.13 Power of the Test, 301

        7.14 Rejection Region and Critical Value, 301

        7.15 p-Value, 302

        7.16 One-Tailed and Two-Tailed Tests, 303

        7.17 Degrees of Freedom, 305

        7.18 Strategy in Selecting the Test Statistic, 306

        7.19 Steps in Hypothesis Testing, 307

        7.20 One-Sample Testing, 312

        7.21 Two-Sample Testing, 324

        7.22 Test of Significance about Two Population Proportions, 338

        7.23 Test of Significance about Two Population Variances, 341

        7.24 Computing with Excel, 346

        8 Analysis of Variance and Designing Research Experiments 375

        8.1 Introduction, 375

        8.2 Understanding Analysis of Variance, 376

        8.3 Design of Experiment, 378

        8.4 One-way Analysis of Variance, 379

        8.5 Completely Randomized Design, 384

        8.6 Two-way Analysis of Variance (N Observations Per Cell), 391

        8.7 Two-way Analysis of Variance (One Observation Per Cell), 397

        8.8 Randomized Block Design, 401

        8.9 Factorial Design, 407

        8.10 Analysis of Covariance, 414

        8.11 Computing with Excel, 428

        9 Understanding Relationships and Developing Regression Models 461

        9.1 Introduction, 461

        9.2 Types of Relationship, 462

        9.3 Correlation Coefficient, 463

        9.4 Partial Correlation, 476

        9.5 Multiple Correlation, 480

        9.6 Suppression Variable, 483

        9.7 Regression Analysis, 485

        9.8 The Multiple Regression Model, 510

        9.9 Different Ways of Testing a Regression Model, 515

        9.10 Law of Diminishing Returns, 523

        9.11 Different Approaches in Developing Multiple Regression Models, 524

        9.12 Computing with Excel, 528

        10 Statistical Tests for Nonparametric Data 556

        10.1 Introduction, 556

        10.2 Merits and Demerits of Nonparametric Tests, 557

        10.3 Chi-Square Test, 557

        10.4 Runs Test, 571

        10.5 Mann–Whitney U-Test for Two Samples, 577

        10.6 Wilcoxon Matched-Pairs Signed-Ranks Test, 584

        10.7 Kruskal–Wallis Test (One-Way ANOVA for Nonparametric Data), 589

        10.8 The Friedman Test, 593

        10.9 Computing with Excel, 599

        11 Measuring Associations in Nonparametric Data 615

        11.1 Introduction, 615

        11.2 Rank Correlation (Measure of Association Between Ranked Data), 616

        11.3 Bi-Serial Correlation (Measure of Association Between a Dichotomous and a Continuous Variable), 622

        11.4 Point Bi-Serial Correlation (Measure of Correlation Between a True Dichotomous Variable and a Continuous Variable), 624

        11.5 Tetrachoric Correlation (Measure of Association Between Dichotomous Variables), 629

        11.6 Phi Coefficient (Measure of Association Between Naturally Dichotomous Variables), 636

        11.7 Contingency Coefficient (Measure of Association Between Categorical Variables), 640

        11.8 Computing with Excel, 646

        12 Developing Norms for Assessing Performance 657

        12.1 Introduction, 657

        12.2 Percentiles, 658

        12.3 Z-Scale, 663

        12.4 T-Scale, 664

        12.5 Stanine Scale, 664

        12.6 Composite Scale Based on Z-Score, 666

        12.7 Scaling of Ratings in Terms of the Normal Curve, 671

        12.8 Developing Norms Based on Difficulty Ratings, 674

        12.9 Computing with Excel, 677

        Appendix: Statistical Tables 688

        Table A.1 Trigonometric Function, 688

        Table A.2 Binomial Probability Distribution, 691

        Table A.3 Poisson Probability Distribution, 695

        Table A.4 The Normal Curve Area Between the Mean and a Given z Value, 700

        Table A.5 Ordinates at Different Values of z-Score in the Standard Normal Distribution, 701

        Table 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), 704

        Table A.7 Critical Values of “t”, 707

        Table A.8 Critical Values of the Correlation Coefficient, 708

        Table A.9 F-Table: Critical Values = 0.05, 709

        Table A.10 F-Table: Critical Values = 0.01, 710

        Table A.11 The Chi-square Table, 711

        Table A.12 Critical Values for Number of Runs R, 712

        Table A.13 Critical Values for the Mann–Whitney U-Test, 713

        Table A.14 Critical Values of T for the Wilcoxon Matched-pairs Signed-ranks Test (Small Samples), 713

        Table A.15 Critical Values of Studentized Range Distribution(q) for Familywise = .05, 714

        Index 717

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