Statistics in Kinesiology
Human Kinetics (Verlag)
978-1-4925-6071-5 (ISBN)
Statistics in Kinesiology, Fifth Edition With Web Resource, offers students in kinesiology and exercise science programs a unique introduction to the statistics concepts and techniques relevant to their specific field of study. Drawing from examples across kinesiology, including exercise physiology, biomechanics, physical education, and physical therapy, this essential text provides students with a statistical skill set that will enable them to analyze quantitative data and find answers to questions they will encounter in their specific disciplines.
As in previous editions, emphasis is placed on methods commonly seen in kinesiology, such as correlation and bivariate regression, t tests, analysis of variance (ANOVA), and the interpretation of interactions in factorial analyses of variance. The fifth edition also incorporates fully updated content reflecting the changing face of kinesiology:
Comparisons of observational versus experimental research and nonparametric versus parametric methods of analyzing categorical and ordinal data
More detailed coverage on how to calculate central tendency when data have been transformed (e.g., log transformations) as well as multiple ways to interpret the correlation coefficient
Expanded coverage of statistical graphs, including dot plots and spaghetti plots
A discussion of the real meaning of p values and confidence intervals
An introduction to frequentist approaches versus Bayesian methods
In addition, a new web resource offers abridged presentations of complex statistical concepts and an interactive platform to practice problem solving. Mini lectures, consisting of narrated slideshows, provide further explanations and may be quickly accessed through QR codes placed at the end of each chapter. Sample problems then provide an opportunity for students to put the concepts into practice.
Statistical software tools commonly used in kinesiology applications—such as JASP and G*Power—are briefly introduced, encouraging students to apply their knowledge of statistical procedures to generate and interpret computer results with confidence and ease.
With Statistics in Kinesiology, Fifth Edition, students will gain a solid understanding of the statistical techniques used in physical activity fields. The book’s practical approach, based on the authors’ more than 50 years of combined experience in teaching statistics, will make it easy for students to learn these important, but often intimidating, concepts.
Joseph P. Weir, PhD, is the chair of the department of health, sport, and exercise sciences at the University of Kansas. From 1995 to 2012 he was a professor in the physical therapy doctorate program at Des Moines University in Iowa. He earned his doctorate in exercise physiology from the University of Nebraska at Lincoln. Weir is a fellow of both the American College of Sports Medicine (ACSM) and the National Strength and Conditioning Association (NSCA). He was given the NSCA President’s Award in 2007 and its William J. Kraemer Outstanding Sport Scientist Award in 2006. He served as president of the National Strength and Conditioning Association Foundation from 2006 to 2009, and he was cochair of the ACSM’s Biostatistics Interest Group from 2001 to 2003. Weir is a senior associate editor of the Journal of Strength and Conditioning Research, and he is a member of the editorial board of Medicine and Science in Sports and Exercise. He is the author of numerous research articles, which have appeared in European Journal of Applied Physiology, Physiological Measurement, American Journal of Physiology, and Journal of Orthopaedic and Sports Physical Therapy. He is coauthor of Physical Fitness Laboratories on a Budget, and he has contributed chapters to seven texts, including NSCA’s Essentials of Personal Training. Weir is originally from Glennallen, Alaska. He and his wife, Loree, live in Lawrence, Kansas, and have three adult children. He is an avid motorcyclist and a fan of University of Nebraska football, University of Kansas basketball, and Boston Bruins hockey. William J. Vincent, EdD, is a retired adjunct professor and former director of the general education wellness program in the department of exercise sciences at Brigham Young University in Provo, Utah. He is a professor emeritus and the former chair of the department of kinesiology at California State University at Northridge (CSUN). He was employed at CSUN for 40 years and taught statistics and measurement theory for 35 of those years. In 1995 he received the university’s Distinguished Teaching Award. Vincent has been a member of the American Alliance for Health, Physical Education, Recreation and Dance (AAHPERD), now SHAPE America, since 1964. In 2007, he received the AAHPERD National Honor Award for distinguished service to the profession. 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. 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, International Journal of Sports Medicine, and Journal of Athletic Training. He has a bachelor’s degree in physical education (pedagogy), a master’s degree in physical education (exercise physiology), and a doctorate in educational psychology (perception and learning), all from the University of California at Los Angeles. Vincent lives in Lindon, Utah. He and his late wife, Diana, raised six children, and he has 24 grandchildren and nine great-grandchildren. In his free time, he enjoys camping, snow skiing and water skiing, conducting genealogical research, and reading.
Chapter 1. Measurement, Statistics, and Research
What Is Measurement?
Process of Measurement
Variables and Constants
Research Design and Statistical Analysis
Statistical Inference
Summary
Chapter 2. Organizing and Displaying Data
Organizing Data
Displaying Data
Summary
Chapter 3. Percentiles
Common Percentile Divisions
Calculations Using Percentiles
Summary
Chapter 4. Measures of Central Tendency
Mode
Median
Mean
Relationships Among the Mode, Median, and Mean
Summary
Chapter 5. Measures of Variability
Range
Interquartile Range
Variance
Standard Deviation
Definition Method of Hand Calculations
Calculating Standard Deviation for a Sample
Coefficient of Variation
Standard Deviation and Normal Distribution
Summary
Chapter 6. The Normal Curve
Z Scores
Standard Scores
Probability and Odds
Calculating Skewness and Kurtosis
Summary
Chapter 7. Fundamentals of Statistical Inference
Predicting Population Parameters Using Statistical Inference
Estimating Sampling Error
Levels of Confidence, Confidence Intervals, and Probability of Error
An Example Using Statistical Inference
Statistical Hypothesis Testing
Type I and Type II Error
Degrees of Freedom
Living With Uncertainty
Two- and One-Tailed Tests
Applying Confidence Intervals
Summary
Chapter 8. Correlation and Bivariate Regression
Correlation
Calculating the Correlation Coefficient
Bivariate Regression
Homoscedasticity
Summary
Chapter 9. Multiple Correlation and Multiple Regression
Multiple Correlation
Partial Correlation
Multiple Regression
Summary
Chapter 10. The t Test: Comparing Means From Two Sets of Data
The t Tests
Types of t Tests
Magnitude of the Difference (Size of Effect)
Determining Power and Sample Size
The t Test for Proportions
Summary
Chapter 11. Simple Analysis of Variance: Comparing the Means Among Three or More Sets of Data
Assumptions in ANOVA
Sources of Variance
Calculating F: The Definition Method
Determining the Significance of F
Post Hoc Tests
Magnitude of the Treatment (Size of Effect)
Summary
Chapter 12. 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
An Example From Leisure Studies and Recreation
Summary
Chapter 13. Quantifying Reliability
Intraclass Correlation Coefficient
Standard Error of Measurement
Summary
Chapter 14. Factorial Analysis of Variance
A Between–Between Example
A Between–Within Example
A Within–Within Example
Summary
Chapter 15. Analysis of Covariance
Relationship Between ANOVA and Regression
ANCOVA and Statistical Power
Assumptions in ANCOVA
The Pretest–Posttest Control Group Design
Pairwise Comparisons
Summary
Chapter 16. 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
Chapter 17. Clinical Measures of Association
Relative Risk
Odds Ratio
Diagnostic Testing
Summary
Chapter 18. Advanced Statistical Procedures
Multilevel Modeling
Meta-Analysis
Multiple Analysis of Variance
Factor Analysis
Discriminant Analysis
Summary
Appendix: Statistical Tables
| Erscheinungsdatum | 17.03.2020 |
|---|---|
| Verlagsort | Champaign, IL |
| Sprache | englisch |
| Maße | 216 x 279 mm |
| Gewicht | 862 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Studium ► 1. Studienabschnitt (Vorklinik) ► Physiologie | |
| Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
| ISBN-10 | 1-4925-6071-5 / 1492560715 |
| ISBN-13 | 978-1-4925-6071-5 / 9781492560715 |
| Zustand | Neuware |
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