Statistics in music education research: a reference for researchers, teachers, and students

From the very beginning, Russell makes clear his goal ‘to mitigate, if not alleviate, some of the apprehensions experienced by so many students’ (xv) when it comes to statistics in music education research. As someone who has at times ‘fumble[d] through this experience’ (xv) myself, I can relate to the need for a text within the field of music education that presents a clear understanding and application of statistical procedures. Russell does just that by framing the material in his text around four main principles of music education research: (a) understanding, (b) critiquing, (c) applying, and (d) reporting. His use of both peer-reviewed publications and data sets from music education make the contextual understanding more ‘real,’ and assist the reader in creating transfers to one’s own research or classroom. Instructors and students alike will appreciate Russell’s application of the material to an authentic setting within music education research. In the first of four sections, Russell presents the essential and fundamental principles of quantitative research—hypothesis testing, variable types, the normal curve, error, descriptive statistics, and a clear explanation of statistical significance. Considering the bulk of the remaining text is divided by parametric and nonparametric statistics, Russell acknowledges the need to address this difference early on. His definitions of both types of procedures are supported by common assumptions for each, discussing the ‘why’ in choosing appropriate data analysis procedures: ‘Nonparametric tests are often ignored by researchers when they should be used when the data do not meet the requisite assumptions for parametric tests’ (23). Considering that many music education students might use this text, instructors will appreciate the directness with which he approaches such rationales and reasoning. In addition to the prose, Russell provides charts and tables that help to illustrate the differences among various methods of statistical analysis (e.g. which test to choose (page 28), research questions answered by each statistical procedure (page 30)). Though some research class instructors may find this to be too much information at the onset (these charts in the Introduction list various statistical procedures yet to be discussed), I tend to like the foreshadowing here. For those using the text as a resource, such visual aids provide a quick reference and help direct the reader to the subsequent chapter (statistical analysis) that applies. Throughout the entirety of Section 1, Russel presents the fundamental concepts of quantitative research with conciseness and clarity. The three remaining sections of the text focus on parametric statistics, reliability analysis, and nonparametric tests. Pick your poison. Russell includes chapters dedicated to all of the common statistical procedures we are used to seeing in music education research: Pearson product-moment correlations, t-tests, the variety of ANOVAs, regression, factor analysis, Chronbach’s alpha, chi-square, Mann-Whitney, and more. Each chapter/topic/analysis follows a similar format. Let us use Chapter 7 on univariate (one-way) ANOVA as an example. Russell begins with a brief discussion of what the procedure is, what it does, and why it might be used. Perhaps what is most appealing about this text is the way in which he uses music examples to illustrate concepts.