Quantitative Research Methods for Linguistics provides an accessible introduction to research methods for undergraduates undertaking research for the first time. Employing a task-based approach, the authors demonstrate key methods through a series of worked examples, allowing students to take a learn-by-doing approach and making quantitative methods less daunting for the novice researcher. Key features include: Chapters framed around real research questions, walking the student step-by-step through the various methods; Guidance on how to design your own research project; Basic questions and answers that every new researcher needs to know; A comprehensive glossary that makes the most technical of terms clear to readers; Coverage of different statistical packages including R and SPSS. Quantitative Research Methods for Linguistics is essential reading for all students undertaking degrees in linguistics and English language studies.
Presents a comprehensive introduction to analysing quantitative linguistic data. Starting with an definition of quantitative data, and how it differs from qualitative data, Seb Rasinger examines what the student linguist is trying to find out through analysing data, and how quantitative techniques can help arrive at meaningful and accurate conclusions. This expanded, 2nd edition now also includes a discussion of Analysis of Variance (ANOVA) and MANOVA, and provides a brief introduction to statistical meta-analysis. A companion website allows readers to download crib sheets and Excel templates for the main statistical tools. The book introduces: -using statistics -variables -reliability of data -describing data -analysing data -testing hypotheses -dealing with problematic data. Each chapter includes graphs and figures explaining theory through worked examples, chapter summaries, and exercises to aid student understanding. An appendix containing a summary of statistical formulae, excel commands and statistical tables is included and is an invaluable resource. Presenting a down-to-earth and readable introduction to quantitative research, this book is a useful how-to guide for students encountering quantitative data for the first time, or for postgraduates embarking on linguistic research projects.
Quantitative Methods in Linguistics offers a practical introduction to statistics and quantitative analysis with data sets drawn from the field and coverage of phonetics, psycholinguistics, sociolinguistics, historical linguistics, and syntax, as well as probability distribution and quantitative methods. Provides balanced treatment of the practical aspects of handling quantitative linguistic data Includes sample datasets contributed by researchers working in a variety of sub-disciplines of linguistics Uses R, the statistical software package most commonly used by linguists, to discover patterns in quantitative data and to test linguistic hypotheses Includes student-friendly end-of-chapter assignments and is accompanied by online resources at available in the 'Downloads' section, below
This is a comprehensive overview of research methodology in applied linguistics which describes the various stages of qualitative and quantitative investigations, from collecting the data to reporting the results.
This book provides practical guidance on research methods and designs that can be applied to Complex Dynamic Systems Theory (CDST) research. It discusses the contribution of CDST to the field of applied linguistics, examines what this perspective entails for research and introduces practical methods and templates, both qualitative and quantitative, for how applied linguistics researchers can design and conduct research using the CDST framework. Introduced in the book are methods ranging from those in widespread use in social complexity, to more familiar methods in use throughout applied linguistics. All are inherently suited to studying both dynamic change in context and interconnectedness. This accessible introduction to CDST research will equip readers with the knowledge to ensure compatibility between empirical research designs and the theoretical tenets of complexity. It will be of value to researchers working in the areas of applied linguistics, language pedagogy and educational linguistics and to scholars and professionals with an interest in second/foreign language acquisition and complexity theory.
An in-depth introduction to all research methods in linguistics, this is the ideal textbook for undergraduate and postgraduate students. Research Methods are important skills for students of linguistics to learn prior to undertaking research projects at either undergraduate or postgraduate level. Students need to learn how to develop research methods appropriate for their chosen study, and how to record, transcribe, code and analyse the data collected. This comprehensive introduction to research methods in linguistics guides the student through these areas, offering advice at a theoretical and practical level. The book covers formal, computational, quantitative and qualitative research methods in detail, and each chapter is written by an academic renowned in the field. Topics covered include: using corpora, questionnaire design, computer-assisted content analysis, interview methods, observation, fieldwork in linguistics, and statistic analysis. Providing an in-depth introduction to all research methods in linguistics, this is the ideal textbook for undergraduate and postgraduate students encountering linguistic data for the first time. Research Methods in Linguistics is a new series from Continuum providing a series of introductions to the quantitative and qualitative research methods needed by undergraduate and postgraduate students. The centre of the series is Research Methods in Linguistics edited by Lia Litosseliti, which provides a comprehensive overview of all the research methods needed by linguistics students. Each book in the series takes one of the research methods described in the general introduction and expands upon this in a book length study.
This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.
This Handbook provides a comprehensive treatment of basic and more advanced research methodologies in applied linguistics and offers a state-of-the-art review of methods particular to various domains within the field. Arranged thematically in 4 parts, across 41 chapters, it covers a range of research approaches, presents current perspectives, and addresses key issues in different research methods, such as designing and implementing research instruments and techniques, and analysing different types of applied linguistics data. Innovations, challenges and trends in applied linguistics research are examined throughout the Handbook. As such it offers an up-to-date and highly accessible entry point into both established and emerging approaches that will offer fresh possibilities and perspectives as well as thorough consideration of best practices. This wide-ranging volume will prove an invaluable resource to applied linguists at all levels, including scholars in related fields such as language learning and teaching, multilingualism, corpus linguistics, critical discourse analysis, discourse analysis and pragmatics, language assessment, language policy and planning, multimodal communication, and translation.
The successful collection of data is a key challenge to obtaining reliable and valid results in applied linguistics research. Data Collection Research Methods in Applied Linguistics investigates how research is conducted in the field, encompassing the challenges and obstacles applied linguists face in collecting good data. The book explores frequently used data collection techniques, including: * interviews and focus groups * observations * stimulated recall and think aloud protocols * data elicitation tasks * corpus methods * questionnaires * validated tests and measures Each chapter focuses on one type of data collection, outlining key concepts, threats to reliability and validity, procedures for good data collection, and implications for researchers. The chapters also include exemplary research projects, showcasing and explaining for readers how the technique was used to collect data in a successfully published study. This book is an essential resource for both novice and experienced applied linguists tackling data collection techniques for the first time.
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.
