This is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into two distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses.
This is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into two distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Moh H. Malek, Ph.D., FACSM, FNSCA, CSCS,*D, is an Associate Professor (tenured) of Physical Therapy in the Department of Health Care Sciences at the Eugene Applebaum College of Pharmacy and Health Sciences at Wayne State University in Detroit, Michigan, USA. Jared W. Coburn, Ph.D., FASCM, FNSCA, CSCS,*D, is a Professor (tenured) of Kinesiology in the Department of Kinesiology at California State University, Fullerton, California, USA. William D. Marelich, Ph.D., is Professor (tenured) of Psychology in the Department of Psychology at California State University, Fullerton, and a consulting statistician for Health Risk Reduction Projects, Integrative Substance Abuse Programs (ISAP), Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles, USA.
Inhaltsangabe
Part 1: ANOVA analysis 1. What's stats got to do with it? 2. Organizing the data 3. Review of one-way analysis of variance (ANOVA) 4. Two- and three-way factorial ANOVA 5. Mixed or between-within factorial ANOVA 6. Analysis of covariance (ANCOVA) Part 2: Regression analysis 7. Diagnostic tests for regression 8. Basic multiple regression analysis 9. Multiple regression models for quantitative and categorical data 10. Regression model validation 11. Logistic regression Part 3: Special statistical procedures 12. Multivariate analysis of variance (MANOVA)
Part 1: ANOVA analysis 1. What's stats got to do with it? 2. Organizing the data 3. Review of one-way analysis of variance (ANOVA) 4. Two- and three-way factorial ANOVA 5. Mixed or between-within factorial ANOVA 6. Analysis of covariance (ANCOVA) Part 2: Regression analysis 7. Diagnostic tests for regression 8. Basic multiple regression analysis 9. Multiple regression models for quantitative and categorical data 10. Regression model validation 11. Logistic regression Part 3: Special statistical procedures 12. Multivariate analysis of variance (MANOVA)
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