In Statistics in Music Education Research, author Joshua Russell offers a new course book that explains the process of using a range of statistical analyses from inception to research design to data entry to final analysis using understandable descriptions and examples from extant music education research.
In Statistics in Music Education Research, author Joshua Russell offers a new course book that explains the process of using a range of statistical analyses from inception to research design to data entry to final analysis using understandable descriptions and examples from extant music education research.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Joshua A. Russell is Associate Professor of Music Education at the Hartt School of the University of Hartford where he currently is Director of the Music Education Division and Chair of Graduate Studies in Music Education. He teaches undergraduate and graduate courses in music education and string pedagogy and is the director of the Hartt String Project. Dr. Russell's research interests include musician health, assessment of music learning, string education, and psycho-social/cognitive development in musical learning and teaching. He often presents research throughout the United States and beyond including Ireland, England, Germany, China, Australia, Finland, Greece, Norway, and Cyprus.
Inhaltsangabe
Preface ix About the Companion Website Section 1: Introduction Chapter 1: Fundamental Principles Chapter 2: Descriptive Statistics Section 2: Parametric Statistical Procedures Chapter 3: Pearson Product Moment Correlation Chapter 4: One Sample T-Test Chapter 5: Dependent Samples T-Test Chapter 6: Independent Samples t-test Chapter 7: Univariate Analysis of Variance (ANOVA) Chapter 8: Factorial ANOVA Chapter 9: Multivariate Analysis of Variance (MANOVA) Chapter 10: Repeated Measures Analysis of Variance Chapter 11: Univariate Analysis of Covariance (ANCOVA) Chapter 12: Multivariate Analysis of Covariance (MANCOVA) Chapter 13: Regression Analysis Chapter 14: Data Reduction: Factor and Principle Component Analysis Chapter 15: Discriminant Analysis Section 3: Reliability Analysis Chapter 16: Cronbach's Alpha Chapter 17: Split-half Reliability Section 4: Nonparametric Tests Chapter 18: Chi-Square Chapter 19: Mann-Whitney U Test Chapter 20: Kruskal Wallis H Test Chapter 21: Spearman Correlation Chapter 22: Wilcoxon Test Chapter 23: Friedman's Test Appendix 406 Index
