Statistics in Music Education Research

by Joshua A. Russell

Overview

In Statistics in Music Education Research, author Joshua Russell 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. He 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; and 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. 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 music education.

Product Details

ISBN-13:	9780190695248
Publisher:	Oxford University Press
Publication date:	01/09/2018
Sold by:	Barnes & Noble
Format:	eBook
Pages:	304
File size:	12 MB
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About the Author

Joshua A. Russell is Associate Professor of Music Education at the Hartt School of the University of Hartford.

Table of Contents

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