Statistics in Kinesiology / Edition 1

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Statistics in Kinesiology, Third Edition, is an introductory text that will help students learn how to use a variety of statistical techniques. The book uses examples and data sets that should be familiar to students majoring in kinesiology and related fields, thus making it easier to learn and apply the statistical concepts.

This new edition contains the following features:
-Updates and revisions that develop statistical techniques in a simpler and clearer way

-Upgraded content with new and extensive problem sets to help students interact with the subject matter

-Techniques that can be applied to kinesiological subdisciplines and that are relevant to the movement sciences Using statistical techniques from physical education, exercise science, administration, and pedagogy, students with basic algebraic skills will be able to interpret data by hand calculation and check their results against computer output. While the text preserves its basic techniques, there is expanded content on computer usage in relation to statistics, which will further enhance understanding and reflect the changes in the field. By gaining knowledge of the mathematical formulas used by software programs, students will learn to critically evaluate computer results and interpret data with greater confidence and ease.

The extensive problem sets, complete with answers, come with key words to identify the content that students should carefully review. The new problem sets in this edition are designed to help students interact more fully with the content and thus more fully learn the concepts and techniques.

In the early chapters, students receive a thorough introduction to measurement, statistics, and research; learn how to organize and display data; and calculate using percentiles. Students then move on to study measures of central tendency and variability, curves and sampling errors, and correlations and different types of regressions. Later they learn how to use t tests and how to analyze variance, comparing means and using repeated measures. Students also learn advanced statistical procedures and how to analyze nonparametric data.

This new edition is highly readable and well illustrated with figures explaining or demonstrating statistical concepts. By using Statistics in Kinesiology, Third Edition, students should gain a firm knowledge on the relevant statistical techniques used in physical activity fields, and professionals have a great reference at their fingertips.

The book contains black-and-white illustrations.

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Product Details

  • ISBN-13: 9780873226998
  • Publisher: Human Kinetics Publishers
  • Publication date: 4/28/1995
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 257

Meet the Author

William J. Vincent, EdD, is currently the director of the General Education Wellness Program in the department of exercise sciences at Brigham Young University in Provo, Utah. He is professor emeritus and former chair of the department of kinesiology at California State University at Northridge. He was employed at CSUN for 39 years and taught statistics and measurement theory for 35 of those years. In 1995 he received the University Distinguished Teaching Award.

Dr. Vincent has been a member of the American Alliance for Health, Physical Education, Recreation and Dance since 1964. He has served as the president of the Southwest District of AAHPERD and was a member of the AAHPERD Board of Governors from 1993 to 1995. In 1988 he was named the Southwest District Scholar and delivered the keynote address titled "From Means to Manova" at the 1989 convention.

Dr. Vincent is the author or coauthor of four books and more than 70 professional articles. Fifty-one of those articles appeared in refereed journals, including Research Quarterly for Exercise and Sport, The International Journal of Sports Medicine, and the Journal of Athletic Training. He has a bachelor's degree in physical education (pedagogy) and a master's degree in physical education (exercise physiology), and he received his doctorate in educational psychology (perception and learning) in 1966 from the University of California at Los Angeles.

Dr. Vincent and his wife, Diana, live in Lindon, Utah, and have 6 children and 14 grandchildren. In his free time, Dr. Vincent enjoys camping, snow skiing and water skiing, off-road motorcycle riding, gardening, and reading.

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Table of Contents

Chapter 1. Measurement, Statistics, and Research What Is Measurement? 
The Process of Measurement 
Variables and Constants 
Research Design and Statistical Analysis 
Statistical Inference 
Problems to Solve 
Key Words

Chapter 2. Organizing and Displaying Data 
Organizing Data 
Displaying Data 
Problems to Solve 
Key Words

Chapter 3. Percentiles 
Common Percentile Divisions 
Calculations Using Percentiles 
Problems to Solve 
Key Words

Chapter 4. Measures of Central Tendency 
The Mode 
The Median 
The Mean 
Relationships Among the Mode, Median, and Mean 
Problems to Solve 
Key Words

Chapter 5. Measures of Variability 
Interquartile Range 
Standard Deviation 
Calculating Standard Deviation for a Sample 
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 
Problems to Solve 
Key Words

Chapter 7. Correlation, Bivariate Regression, and Multiple Regression 
Calculating the Correlation Coefficient 
Bivariate Regression 
Multiple Regression 
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
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)
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
Problems to Solve
Key Words

Chapter 11. Factorial Analysis of Variance
A Between-Between Example
A Between-Within Example
A Within-Within Example
Key Words

Chapter 12. Advanced Statistical Procedures
Analysis of Covariance
Multiple Analysis of Variance
Factor Analysis
Discriminant Analysis
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
Problems to Solve
Key Words

Appendix A Statistical Tables
Appendix B Raw Data
Appendix C Answers to Problems

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