Statistics For Linguistics With R

Author: Stefan Th. Gries
Publisher: Walter de Gruyter
ISBN: 3110307472
Size: 34.24 MB
Format: PDF, ePub, Docs
View: 1617
Download Read Online

Statistics For Linguistics With R from the Author: Stefan Th. Gries. This book is the revised and extended second edition of Statistics for Linguistics with R. The volume 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. Just like the first edition, it is aimed at students, faculty, and researchers with little or no statistical background in statistics or the open source programming language R. It avoids mathematical jargon and discusses the logic and structure of quantitative studies and introduces descriptive statistics as well as a range of monofactorial statistical tests for frequencies, distributions, means, dispersions, and correlations. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, a revision of overview sections on statistical tests and regression modeling, a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA, and a new visual tool to identify the right statistical test for a given problem and data set. The amount of code available from the companion website has doubled in size, providing much supplementary material on statistical tests and advanced plotting.

Quantitative Corpus Linguistics With R

Author: Stefan Th. Gries
Publisher: Taylor & Francis
ISBN: 1317597664
Size: 65.36 MB
Format: PDF, ePub, Docs
View: 529
Download Read Online

Quantitative Corpus Linguistics With R from the Author: Stefan Th. Gries. As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on: data processing and manipulation in general; text processing with and without regular expressions of large bodies of textual and/or literary data, and; basic aspects of statistical analysis and visualization. This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.

Quantitative Research Methods In Translation And Interpreting Studies

Author: Christopher D. Mellinger
Publisher: Taylor & Francis
ISBN: 131729923X
Size: 73.87 MB
Format: PDF, ePub
View: 4289
Download Read Online

Quantitative Research Methods In Translation And Interpreting Studies from the Author: Christopher D. Mellinger. Quantitative Research Methods in Translation and Interpreting Studies encompasses all stages of the research process that include quantitative research methods, from conceptualization to reporting. In five parts, the authors cover: • sampling techniques, measurement, and survey design; • how to describe data; • how to analyze differences; • how to analyze relationships; • how to interpret results. Each part includes references to additional resources and extensive examples from published empirical work. A quick reference table for specific tests is also included in the appendix. This user-friendly guide is the essential primer on quantitative methods for all students and researchers in translation and interpreting studies. Accompanying materials are available online, including step-by-step walkthroughs of how analysis was conducted, and extra sample data sets for instruction and self study: https://www.routledge.com/9781138124967. Further resources for Translation and Interpreting Studies are available on the Routledge Translation Studies Portal: http://cw.routledge.com/textbooks/translationstudies.

The Development Of Latin Clause Structure

Author: Lieven Danckaert
Publisher: Oxford University Press
ISBN: 0191077410
Size: 53.31 MB
Format: PDF, ePub
View: 5784
Download Read Online

The Development Of Latin Clause Structure from the Author: Lieven Danckaert. This book examines Latin word order, and in particular the relative ordering of i) lexical verbs and direct objects (OV vs VO) and ii) auxiliaries and non-finite verbs (VAux vs AuxV). In Latin these elements can freely be ordered with respect to each other, whereas the present-day Romance languages only allow for the head-initial orders VO and AuxV. Lieven Danckaert offers a detailed, corpus-based description of these two word order alternations, focusing on their diachronic development in the period from c. 200 BC until 600 AD. The corpus data reveal that some received wisdom needs to be reconsidered: there is in fact no evidence for any major increase in productivity of the order VO during the eight centuries under investigation, and the order AuxV only becomes more frequent in clauses with a modal verb and an infinitive, not in clauses with a BE-auxiliary and a past participle. The book also explores a more fundamental question about Latin syntax, namely whether or not the language is configurational, in the sense that a phrase structure grammar (with 'higher-order constituents' such as verb phrases) is needed to describe and analyse Latin word order patterns. Four pieces of evidence are presented that suggest that Latin is indeed a fully configurational language, despite its high degree of word order flexibility. Specifically, it is shown that there is ample evidence for the existence of a verb phrase constituent. The book thus contributes to the ongoing debate regarding the status of configurationality as a language universal.

Automatic Treatment And Analysis Of Learner Corpus Data

Author: Ana DĂ­az-Negrillo
Publisher: John Benjamins Publishing Company
ISBN: 9027270953
Size: 45.84 MB
Format: PDF, ePub
View: 5179
Download Read Online

Automatic Treatment And Analysis Of Learner Corpus Data from the Author: Ana DĂ­az-Negrillo. This book is a critical appraisal of recent developments in corpus linguistics for the analysis of written and spoken learner data. The twelve papers cover an introductory critical appraisal of learner corpus data compilation and development (section 1); issues in data compilation, annotation and exchangeability (section 2); automatic approaches to data identification and analysis (section 3); and analysis of learner corpus data in the light of recent models of data analysis and interpretation, especially recent automatic approaches for the identification of learner language features (section 4). This collection is aimed at students and researchers of corpus linguistics, second language acquisition studies and quantitative linguistics. It will significantly advance learner corpus research in terms of methodological innovation and will fill in an important gap in the development of multidisciplinary approaches (for learner corpus studies).

The Handbook Of Linguistics

Author: Mark Aronoff
Publisher: John Wiley & Sons
ISBN: 1405186763
Size: 33.68 MB
Format: PDF, Mobi
View: 3923
Download Read Online

The Handbook Of Linguistics from the Author: Mark Aronoff. "The Handbook of Linguistics is a general introductory volume designed to address this gap in knowledge about language"--

Corpus Linguistics

Author: Anke LĂĽdeling
Publisher: Walter de Gruyter
ISBN: 3110213885
Size: 49.26 MB
Format: PDF, Kindle
View: 2250
Download Read Online

Corpus Linguistics from the Author: Anke LĂĽdeling. This handbook provides an up-to-date survey of corpus linguistics. Spoken, written, and multimodal corpora serve as the bases for quantitative and qualitative research on many issues of linguistic interest. The two volumes together comprise 61 articles by renowned experts from around the world. They sketch the history of corpus linguistics and its relationship with neighbouring disciplines, show its potential, discuss its problems, and describe various methods of collecting, annotating, and searching corpora, as well as processing corpus data. Key features: up-to-date and complete handbook includes both an overview and detailed discussions gathers together a great number of experts

Corpus Pragmatics

Author: Karin Aijmer
Publisher: Cambridge University Press
ISBN: 1107015049
Size: 70.10 MB
Format: PDF, ePub, Mobi
View: 4456
Download Read Online

Corpus Pragmatics from the Author: Karin Aijmer. The first handbook to survey and expand the burgeoning field of corpus pragmatics, the intersection of pragmatics and corpus linguistics.

Doing Applied Linguistics

Author: Nicholas Groom
Publisher: Taylor & Francis
ISBN: 1136672133
Size: 48.48 MB
Format: PDF
View: 1495
Download Read Online

Doing Applied Linguistics from the Author: Nicholas Groom. Doing Applied Linguistics provides a concise, lively and accessible introduction to the field of applied linguistics for readers who have little or no prior knowledge of the subject. The book explores the basics of the field then goes on to examine in more depth what applied linguists actually do, and the types of research methods that are most frequently used in the field. By reading this book students will find the answers to four sets of basic questions: What is applied linguistics, and what do applied linguists do? Why do it? What is the point of applied linguistics? How and why might I get involved in applied linguistics? How to do it? What kinds of activities are involved in doing applied linguistic research? Written by teachers and researchers in applied linguistics Doing Applied Linguistics is essential reading for all students with interests in this area.

Modeling Techniques In Predictive Analytics

Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133886190
Size: 80.76 MB
Format: PDF, ePub, Mobi
View: 7066
Download Read Online

Modeling Techniques In Predictive Analytics from the Author: Thomas W. Miller. To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more