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Geared towards students without advanced mathematical skills, this text examines aspects of statistical analysis that are used in professions and disciplines of kinesiology and leisure studies. It uses examples from kinesiology and related fields to present statistical concepts and procedures.

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• Chapter 1 Measurement, Statistics, and Research
• What Is Measurement?
• The Process of Measurement
• Variables and Constants
• Research Design and Statistical Analysis
• Statistical Inference
• Summary
• Problems to Solve
• Key Words
• Chapter 2 Organizing and Displaying Data
• Organizing Data
• Displaying Data
• Summary
• Problems to Solve
• Key Words
• Chapter 3 Percentiles
• Common Percentile Divisions
• Calculations Using Percentiles
• Summary
• Problems to Solve
• Key Words
• Chapter 4 Measures of Central Tendency
• The Mode
• The Median
• The Mean
• Relationships Among the Mode, Median, and Mean
• Summary
• Problems to Solve
• Key Words
• Chapter 5 Measures of Variability
• Range
• Interquartile Range
• Variance
• Standard Deviation
• Calculating Standard Deviation for a Sample
• Summary
• Problems to Solve
• Key Words
• Chapter 6 The Normal Curve and Sampling Error
• Z Scores
• Standard Scores
• Predicting Population Parameters Using Statistical Inference
• Estimating Sampling Error
• Levels of Confidence and Probability of Error
• Calculating Skewness and Kurtosis
• Summary
• Problems to Solve
• Key Words
• Chapter 7 Correlation, Bivariate Regression, and Multiple Regression
• Correlation
• Calculating the Correlation Coefficient
• Bivariate Regression
• Multiple Regression
• Summary
• Problems to Solve
• Key Words
• Chapter 8 The t Test: Comparing Means From Two Sets of Data
• t Tests
• Assumptions for the t Test
• Comparing Two Independent Samples (A Between Comparison)
• Repeated Measures Design (A Within Comparison)
• The Magnitude of the Difference (Size of Effect)
• Type I and Type II Errors
• Two- and One-Tailed Tests
• Determining Power and Sample Size
• The t Test for Proportions
• Summary
• Problems to Solve
• Key Words
• Chapter 9 Simple Analysis of Variance: Comparing the Means Among Three or More Sets of Data
• Assumptions in ANOVA
• Sources of Variance
• Calculating F
• Determining the Significance of F
• Post Hoc Tests
• The Magnitude of the Treatment (Size of Effect)
• Summary
• Problems to Solve
• Key Words
• Chapter 10 Analysis of Variance With Repeated Measures
• Assumptions in Repeated Measures ANOVA
• Calculating Repeated Measures ANOVA
• Correcting for Violations of the Assumption of Sphericity
• Post Hoc Tests
• Interpreting the Results
• Intraclass Reliability
• Summary
• Problems to Solve
• Key Words
• Chapter 11 Factorial Analysis of Variance
• A Between-Between Example
• A Between-Within Example
• A Within-Within Example
• Summary
• Key Words
• Chapter 12 Advanced Statistical Procedures
• Analysis of Covariance
• Multiple Analysis of Variance
• Factor Analysis
• Discriminant Analysis
• Summary
• Key Words
• Chapter 13 Analysis of Nonparametric Data
• Chi-Square (Single Classification)
• Chi-Square (Two or More Classifications)
• Rank Order Correlation
• Mann-Whitney U Test
• Kruskal-Wallis ANOVA for Ranked Data
• Friedman's Two-Way ANOVA by Ranks
• Summary
• Problems to Solve
• Key Words
• Appendix A Statistical Tables
• Appendix B Raw Data
• Appendix C Answers to Problems
• Glossary
• References
• Index
• About the Author