Statistics in Music Education Research

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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

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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. This book, the first on the topic for graduate students in music education courses, explores four main aspects of music education research: understanding logical concepts of statistical procedures and their outcomes; critiquing the use of different procedures in extant and developing research; applying the correct statistical model for not only any given dataset, but also the correct logic determining which model to employ; reporting the results of a given statistical procedure clearly and in a way that provides adequate information for the reader to determine if the data analysis is accurate and interpretable. Written in a manner that neither intimidates nor condescends music educators in graduate school, Statistics in Music Education Research gives readers a functioning understanding of the statistical procedure discussed in the chapter as well as the tools needed to identify the correctness of use and the ability to apply the statistical procedure in their own research. While it is written predominately for graduate students in music education courses, Statistics in Music Education Research will also help music education researchers and teachers of music educators gain a better understanding of how parametric statistics are employed and interpreted in the social science field of music education.

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