Assuming 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 of the data distribution, the text includes sample studies to illustrate the important points in each chapter and exercises to promote understanding of the concepts and the development of practical research skills. Mathematical operations are explained in detail, and step-by-step illustrations in the use of R (a very powerful, online, freeware program) to perform all calculations are provided.
A Companion Website extends and enhances the text with PowerPoint presentations illustrating how to carry out calculations and use R; practice exercises with answer keys; data sets in Excel MS-DOS format; and quiz, midterm, and final problems with answer keys.
Rezensionen / Stimmen
"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 Jyvaeskylae, 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
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Illustrationen
35 s/w Tabellen
35 Tables, black and white
Maße
Höhe: 229 mm
Breite: 152 mm
Gewicht
ISBN-13
978-0-415-81994-7 (9780415819947)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Jean L. Turner is Professor, TESOL/TFL Program, Monterey Institute of International Studies, USA.
Autor*in
Monterey Institute of International Studies, USA
Preface
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
