Description
Book SynopsisAssuming no familiarity with statistical methods, this text for language education research methods and statistics courses provides detailed guidance and instruction on principles of designing, conducting, interpreting, reading, and evaluating statistical research done in classroom settings or with a small number of participants. While three different types of statistics are addressed (descriptive, parametric, non-parametric) the emphasis is on non-parametric statistics because they are appropriate when the number of participants is small and the conditions for use of parametric statistics are not satisfied. The emphasis on non-parametric statistics is unique and complements the growing interest among second and foreign language educators in doing statistical research in classrooms. Designed to help students and other language education researchers to identify and use analyses that are appropriate for their studies, taking into account the number of participants and the shape
Trade Review
"The clear and systematic writing style and many concrete examples from language education research make this book an excellent entry point to quantitative research for even those who might be afraid of statistics. Its coverage of non-parametric statistics is particularly useful."
Ari Huhta, University of Jyväskylä, Finland
"This book helps readers to understand basic statistical logics and principles, and to analyze and interpret their data using, the freeware statistical program R, available online. It is suitable for language teachers who may not be satisfied with statistical resources that have many intimidating numbers and formulas but without relevant language learning and teaching contexts"
Sun-Young Shin, Indiana University, Bloomington, USA
The strength of Turner’s book is that it never loses sight of the target audience: language teachers or novice researchers who want to conduct research in their individual contexts with nonrandom and small or unequal samples sizes, which are likely to require the application of nonparametric statistical procedures. In addition, those without access to expensive software like SPSS or with limited knowledge of how to get started using the free software R will find this book an invaluable addition to their personal library."
Aaron C. Sponseller, JALT Journal
Table of ContentsPreface
Acknowledgements
Section I: Foundations
Chapter One: What is research?
Chapter Two: Defining and describing variables
Chapter Three: Designing sound research--variable roles, threats to validity, and research design
Chapter Four: How are research questions formed and what are the parts of well-written research reports?
Chapter Five: What is logical about statistical logic and what purposes does it serve?
Section II: Analyzing Differences Between Two Sets of Data
Chapter Six: The parametric t-test statistics
Chapter Seven: The non-parametric Mann-Whitney U Test and Wilcoxon Signed Rank Test statistics
Section III: Analyzing Differences Among more than Two Sets of Data
Chapter Eight: Introduction to the parametric between-group analysis of variance statistic (ANOVA)
Chapter Nine: The non-parametric Kruskal-Wallis and Friedman's Test statistics
Section IV: Analyzing Patterns within a Variable and Between Two Variables
Chapter Ten: The parametric Pearson’s Product Moment Correlation Coefficient statistic
Chapter Eleven: The non-parametric Spearman’s Rho and Kendall's Tau statistics
Chapter Twelve: The non-parametric Chi-Squared statistics
References
