Essential Statistics For Applied Linguistics

Using numbers and research methods in your studies can be a little daunting at first. This book gives you straightforward guidance and no-nonsense advice on using, analysing and interpreting statistics and methodologies in empirical work. Each topic is introduced by an activity to help stimulate thought, and this is followed by a full explanation and exercises. Essential Statistics for Applied Linguistics: – explores different types of research and explains how to choose a methodology – gives clear explanations of statistical and mathematical terms – builds confidence and skills through hands-on exercises, examples and 'how-to' sections – offers online learning resources, including demonstrations with real data to be used with the software package SPSS Assuming no previous knowledge of methodology and statistics, this book will help you to acquire and strengthen your understanding, practice what you have learnt and feel comfortable with applying this new expertise to your own work.

Assuming no prior knowledge, this text provides a concise, practical and accessible introduction to using, analysing and interpreting statistics and methodologies in empirical work using R or JASP. It takes an activity-based approach, in which students are first stimulated to consider a problem or question and find their own solution before the conventional way of solving that problem or question is introduced. 'How To' guides on R and JASP, which take students step-by-step through statistical analyses and practical assignments, are available on the book's companion website. This book will be an invaluable resource for undergraduate and postgraduate students of applied linguistics. New to this Edition: - Now focuses on R and JASP, two increasingly popular open source softwares used by linguists - 'How To' guides to help students strengthen their understanding and apply what they have learnt available on a companion site - Contains more comprehensive coverage of effect sizes, basic methods, regression theory, relationship studies and non-parametric tests

Statistics in Language Research gives a non-technical but more or less complete treatment of Analysis of Variance (ANOVA) for language researchers. ANOVA is the most frequently used technique when handling the outcomes of research designs with more than two treatments or groups. This technique is used in all parts of linguistics which deal with observations obtained in survey studies and in (quasi-)experimental research, like applied linguistics, psycholinguistics, sociolinguistics, language and speech pathology and phonetics. Most statistical textbooks in the social sciences take examples typical of their own field and, in addition, omit subjects which are particularly relevant for language researchers, like power analysis, quasi F, F1, F2 and minF'. This book offers a thorough introduction to the basic principles of analysis of variance, based on examples taken from language research, and goes beyond the conventional topics treated in introductory textbooks, as it covers topics like 'violations of assumptions', 'missing data', 'problems in repeated measures designs', 'alternatives to analysis of variance' (such as randomization tests and multilevel analysis). Each chapter consists of four sections: treatment of the subject under discussion, a summary of relevant terms and concepts, a section devoted to reporting statistics, and finally an exercise section. After the first introductory chapter, in which fundamental concepts like 'variables', 'cases' and SPSS data formats are presented, the book continues with two 'refreshment' chapters, in which the principles of statistical testing are revised, focusing on the well-known t test. These chapters also deal with the essential, but often neglected concepts of 'statistical power' and 'sample size'. In every chapter examples of SPSS input and output are given.

This book provides language teachers with guidelines to develop suitable listening tests.

'A dictionary of research methodology and statistics in applied linguistics' is a reference guide which offers an authoritative and comprehensive overview of key terms and concepts in the areas of research and statistics as concerns the field of applied linguistics. The volume is intended as a resource to delineate the meaning and use of various concepts, approaches, methods, designs, techniques, tools, types, and processes of applied linguistics research in an efficient and accessible style. Some entries relating to statistical aspects of research are also used so as to help the researcher in the successful formulation, analysis, and execution of the research design and carry the same towards its logical end. This book makes use of approximately 2000 entries on the key concepts and issues of research with cross references where necessary. This volume is designed to appeal to undergraduate and graduate students, teachers, lecturers, practitioners, researchers, consultants, and consumers of information across the field of applied linguistics and other related disciplines.

Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.

This book is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. The volume is aimed at beginners on every level of linguistic education: undergraduate students, graduate students, and instructors/professors and can be used in any research methods and statistics class for linguists. It presupposes no quantitative/statistical knowledge whatsoever and, unlike most competing books, begins at step 1 for every method and explains everything explicitly.