Advanced Statistics for Kinesiology and Exercise Science

<p><em>Advanced Statistics for Kinesiology and Exercise Science</em> is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into three distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses, including chapters on:</p><ul> <p> </p> <li>preparing data for analysis;</li> <p> </p> <li>one-way, factorial, and repeated-measures ANOVA;</li> <p> </p> <li>analysis of covariance and multiple analyses of variance and covariance;</li> <p> </p> <li>diagnostic tests;</li> <p> </p> <li>regression models for quantitative and qualitative data;</li> <p> </p> <li>model selection and validation;</li> <p> </p> <li>logistic regression</li> </ul><p>Drawing clear lines between the use of IBM SPSS Statistics software and interpreting and analyzing results, and illustrated with sport and exercise science-specific sample data and results sections throughout, the book offers an unparalleled level of detail in explaining advanced statistical techniques to kinesiology students. <i>Advanced Statistics for Kinesiology and Exercise Science</i> is an essential text for any student studying advanced statistics or research methods as part of an undergraduate or postgraduate degree programme in kinesiology, sport and exercise science, or health science.</p> <p>Part 1: ANOVA analysis</p><p>1. What’s stats got to do with it?</p><p>2. Organizing the data</p><p>3. Review of one-way analysis of variance (ANOVA)</p><p>4. Two- and three-way factorial ANOVA</p><p>5. Mixed or between-within factorial ANOVA</p><p>6. Analysis of covariance (ANCOVA)</p><p>Part 2: Regression analysis</p><p>7. Diagnostic tests for regression</p><p>8. Basic multiple regression analysis</p><p>9. Multiple regression models for quantitative and categorical data</p><p>10. Regression model validation</p><p>11. Logistic regression</p><p>Part 3: Special statistical procedures</p><p>12. Multivariate analysis of variance (MANOVA)</p>