Book Review

Using Statistics in Small-Scale

Language Education Research: Focus
on Non-Parametric Data
Jean L. Turner, ESL & Applied Linguistics ProfessionalSeries. New York, NY: Routledge. (2014) (344 pp.) ISBN:
9780415819947 Price $53.90 (5,630 yen)
Reviewed by D.S. Bowyer
Nagoya Gakuin University
The ESL & Applied Linguistics Professional Series, published by Routledge, isa wide-ranging series containing some 84 manuscripts covering the entirety of
second-language theory and research. Each volume is designed to act as a primary
textbook in a graduate course or as a personal training manual for professional
development. Turner’s Using Statistics in Small-Scale Language Education
Research: Focus on Non-Parametric Data is a research-oriented addition to the series
which will be appreciated by those aiming to improve their practical knowledge
in second language research methods. The books in this series are highly detailed
with a focus on practical examples, and this volume is no exception.
As noted by the author, a large amount of second language research is
conducted by educator-researchers, typically with their own classes. This bookis aimed specifically at people conducting research in these situations, with aheavy focus on non-parametric statistics and the R software package, a statisticalanalysis program that is free to download and use. Non-parametric statistics
are used for analyzing small (n<30) and/or non-random sets of data (Hatch& Lazaraton, 1991). A single high-school class would be a good example, as50

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they typically contain a group of around 30 students who were not randomly
selected by the researcher. Parametric statistics are more powerful than their
non-parametric cousins but have strict requirements for their use that typicallyrequire large, randomized trials. As Plonsky (2013) noted, quantitative statistics
are often poorly employed in second language studies, with a noticeable lackof the basic conditions required for high quality research. Even in cases wherestatistical methods are appropriate, under-reporting of important data iscommon (Larsen-Hall & Plosky, 2015). I have seen many presentations andresearch papers that employed statistical methods that were inappropriate for theresearch in question, so this book is surely a welcome addition.
The key contribution of this book is its unique focus on non-parametricmethods, which I would argue are usually the most appropriate for second
language research. With the recent rise of mixed methods approaches(quantitative and qualitative together) and action research (very small-scale,practical research) (Onwuegbuzie & Collins, 2007), this volume is likely tofind a large and appreciative audience. The book is intended to take readerswith little knowledge and bring them to practical mastery of the most usefulstatistical methods. The first section, Foundations, addresses research design anddescriptive statistics. Section II, Analyzing Differences Between Two Sets of Data,focuses on t-tests used with parametric statistics and Wilcoxon tests for nonparametric statistics. Section III is titled Analyzing Differences Among More Than
Two Sets of Data and takes the reader through ANOVA used with parametrictests, and Kruskal-Wallis and Friedman’s tests for non-parametric statistics. The
fourth and final section, Analyzing Patterns Within a Variable and Between
Variables, considers the use of the correlational tests Pearson’s PMC, Spearman’srho, Kendall’s tau and Chi-squared tests.
Going into more detail, the first section, Foundations, deals with thebasic concepts of sound research and descriptive statistics, providing detailed
explanations and examples; three published studies in the university context
are used to explain the different types of research that may be appropriate foreducator-researchers. The following two sections take the reader through thevarious parametric and non-parametric methods, providing highly detailed
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explanations of the theoretical background behind each method mentionedabove and an illustrated, step-by-step guide to employing them in R. Turner
does a good job of staying away from overly technical language and also provides
extra online training materials. These downloadable materials (www.routledge.
com/cw/turner) provide a refresher on the key points from the book, alongwith example tests, practice datasets and answer keys for the end-of-chapter
assignments.
The book’s key strengths, namely the incredible level of detail into the how’s
and why’s of each method, and step-by-step practical instructions are a doubleedged sword that results in a dense 344-page tome. By comparison, Lowie andSeton’s (2013) Essential Statistics for Applied Linguistics, which also covers bothparametric and non-parametric statistics, is less than half the length. For thisreason, I would recommend that non-experts like myself pair Turner’s workwith one of the more general reference texts such as Dörnyei’s (2007) Research
Methods in Applied Linguistics. Ultimately, Using Statistics in Small-Scale
Language Education Research: Focus on Non-Parametric Data is an excellent
training manual for both aspiring second-language researchers and those wishing
to brush up on their research skills.

References

Dörnyei, Z. (2007). Research methods in applied linguistics. Oxford UniversityPress.
Hatch, E. M., & Lazaraton, A. (1991). The research manual: Design and statistics
for applied linguistics. Heinle & Heinle.
Larson-Hall, J., & Plonsky, L. (2015). Reporting and interpreting quantitative
research findings: What gets reported and recommendations for the field.
Language Learning, 65(S1), 127–159. https://doi.org/10.1111/lang.12115
Lowie, L., & Seton, B. (2013). Essential statistics for applied linguistics. Red
Globe Press.
Onwuegbuzie, A. J., & Collins, K. M. (2007). A typology of mixed methods
sampling designs in social science research. The Qualitative Report, 12(2),281–316.
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Using Statistics in Small-Scale Language Education Research, OnCUE 13(1), pages50-53

Plonsky, L. (2013). Study quality in SLA: An assessment of designs, analyses,
and reporting practices in quantitative L2 research. Studies in Second
Language Acquisition, 35(4), 655–687. https://doi.org/10.1017/S0272263113000399

Author bio

David Scott Bowyer currently lectures in English at Nagoya Gakuin University.
He is also a PhD candidate at Nagoya University of Foreign Languages, where heis conducting research on the applications of neuroscience and Complex Dynamic
Systems Theory to language learning. <scottybowyer1@gmail.com>
Received: March 11, 2020
Accepted: April 18, 202053