Quantitative Methods for Second Language Research: A Problem-Solving Approach (New Perspectives on Language Assessment) - Tapa dura

Críticas

"This book affords beginning applied linguists an enjoyable journey through all important inferential tests to regression analysis. With their clear style, a wealth of language learning and testing examples, and online SPSS exercises, the authors make it easy to become statistics savvy and learn to love statistics. A fantastic resource!"
Lourdes Ortega, Georgetown University, USA

"Quantitative Methods for Second Language Research cuts through the mathematical jargon of statistical analysis and teaches researchers the necessary skills to carry out quantitative studies in applied linguistics. With real case studies and a problem-solving approach, it is a must-have resource for those who are embarking on quantitative research for the first time."
Heath Rose, The University of Oxford, UK

"In each of their coverage of twelve commonly used parametric and non-parametric statistical procedures, the authors discuss assumptions, significance testing, effect sizes, and SPSS examples. The straightforward writing style, practical problem-solving approach, and companion website make this book accessible and useful for beginners and veteran quantitative researchers alike."
James Dean Brown, The University of Hawai’i at Manoa, USA

Reseña del editor

Quantitative Methods for Second Language Research introduces approaches to and techniques for quantitative data analysis in second language research, with a primary focus on second language learning and assessment research. It takes a conceptual, problem-solving approach by emphasizing the understanding of statistical theory and its application to research problems while paying less attention to the mathematical side of statistical analysis. The text discusses a range of common statistical analysis techniques, presented and illustrated through applications of the IBM Statistical Package for Social Sciences (SPSS) program. These include tools for descriptive analysis (e.g., means and percentages) as well as inferential analysis (e.g., correlational analysis, t-tests, and analysis of variance [ANOVA]). The text provides conceptual explanations of quantitative methods through the use of examples, cases, and published studies in the field. In addition, a companion website to the book hosts slides, review exercises, and answer keys for each chapter as well as SPSS files. Practical and lucid, this book is the ideal resource for data analysis for graduate students and researchers in applied linguistics.