Analyzing Linguistic Data

A Practical Introduction to Statistics using R

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Author: R. H. Baayen

Publisher: Cambridge University Press

ISBN: 1139470736

Category: Language Arts & Disciplines

Page: N.A

View: 1735

Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.

Verstehen und Verständlichkeit juristisch-fachsprachlicher Texte

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Author: Sascha Wolfer

Publisher: Narr Francke Attempto Verlag

ISBN: 3823391526

Category: Literary Criticism

Page: 312

View: 5398

Juristische Texte sind schwer zu verstehen, insbesondere – aber nicht nur – für juristische Laien. Dieser Band beleuchtet diese These ausgehend von linguistischen Verständlichkeitsmodellen und kognitionswissenschaftlichen Modellen der menschlichen Textverarbeitung. Anhand von Aufzeichnungen von Blickbewegungen beim Lesen, einem sogenannten Lesekorpus, werden umfangreiche statistische Modelle berechnet. Diese geben Auskunft über Fragen psycholinguistischer Grundlagenforschung auf der Wort-, Satz- und Textebene. Ferner untersucht er, wie sich Auswirkungen von Reformulierungen auf den Verstehensprozess auswirken. Dabei stehen bekannte Komplexitätsmarker deutscher juristischer Texte im Fokus: Nominalisierungen, komplexe Nominalphrasen und syntaktisch komplexe Texte.

Experimental Research Methods in Sociolinguistics

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Author: Katie Drager

Publisher: Bloomsbury Publishing

ISBN: 147425179X

Category: Language Arts & Disciplines

Page: 216

View: 5667

An accessible, user-friendly guide to the variety of different experimental methods used in sociolinguistics, Experimental Research Methods in Sociolinguistics walks students through the "how-to†? of experimental methods used to investigate variation in both speech production and perception. Focusing squarely on practice and application, it takes the reader from defining a research question, to choosing an appropriate framework, to completing a research project. Featuring a companion website with information on experiment-friendly software, sample experiments and suggestions for work to undertake, the book also covers: -Ethical concerns -How to measure production and perception -How to construct and use corpora

TRENDS IN PHONETICS AND PHONOLOGY. STUDIES FROM GERMAN-SPEAKING EUROPE

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Author: Adrian Leemann,Marie-José Kolly,Stephan Schmid,Volker Dellwo

Publisher: Peter Lang

ISBN: 3035108692

Category: Language Arts & Disciplines

Page: 408

View: 9403

This volume was inspired by the 9th edition of the Phonetik & Phonologie conference, held in Zürich in October 2013. It includes state of the art research on phonetics and phonology in various languages and from interdisciplinary contributors. The volume is structured into the following eight sections: segmentals, suprasegmentals, articulation in spoken and sign language, perception, phonology, crowdsourcing phonetic data, second language speech, and arts (with inevitable overlap between these areas).

Morphologisch komplexe Wörter

Prosodische Struktur und phonetische Realisierung

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Author: Pia Bergmann

Publisher: Language Science Press

ISBN: 396110106X

Category: German language

Page: 437

View: 1774

Many researchers assume that the relation between morphology and phonology is not a direct one but is modulated by prosodic constituents, particularly the phonological word. Despite the theoretical relevance of the phonological word in morphophonology, phonetic investigations of the realization of (complex) words are still rare. The book aims to shed some light on this issue. On the basis of about 3800 tokens from experimentally elicited and spontaneous German speech, it investigates the prosodic boundary phenomena glottal stop insertion / glottalization and degemination, as well as durational reductions and /t/-deletions in the vicinity of a morphological and/or prosodic boundary. Informed by findings from usage-based accounts of language, it systematically introduces token frequency and other potentially influencing factors into the analysis. The results yield a rather complex picture that, on the whole, corroborates the relevance of the phonological word as an interface domain between morphology and phonology. At the same time, the results underline the necessity to consider usage-based factors such as frequency, thus all in all lending support to so-called hybrid models of language.

Advancing Quantitative Methods in Second Language Research

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Author: Luke Plonsky

Publisher: Routledge

ISBN: 1317974085

Category: Language Arts & Disciplines

Page: 358

View: 3337

Advancing Quantitative Methods in Second Language Research is the first hands-on guide to conducting advanced research methods in the fields of applied linguistics and second language studies. While a number of texts discuss basic quantitative research methodology, none focus exclusively on providing coverage of alternative advanced statistical procedures in second language studies from a practical approach. The text is bookended by discussions of these advanced procedures in the larger context of second language studies, debating their strengths, weaknesses, and potential for further research; the remaining chapters are how-to sections, each chapter following the same organization, on a wide variety of advanced research methods. By offering much-needed coverage on advanced statistical concepts and procedures, with an eye toward real-world implementation, Advancing Quantitative Methods in Second Language Research enhances the methodological repertoire of graduate students and researchers in applied linguistics and second language studies. For additional content, visit: http://oak.ucc.nau.edu/ldp3/AQMSLR.html

Text Analysis with R for Students of Literature

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Author: Matthew L. Jockers

Publisher: Springer

ISBN: 3319031643

Category: Computers

Page: 194

View: 9855

Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.

The Oxford Handbook of Derivational Morphology

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Author: Rochelle Lieber,Pavol Stekauer

Publisher: OUP Oxford

ISBN: 0191651788

Category: Language Arts & Disciplines

Page: 768

View: 3400

The Oxford Handbook of Derivational Morphology is intended as a companion volume to The Oxford Handbook of Compounding (OUP 2009) Written by distinguished scholars, its 41 chapters aim to provide a comprehensive and thorough overview of the study of derivational morphology. The handbook begins with an overview and a consideration of definitional matters, distinguishing derivation from inflection on the one hand and compounding on the other. From a formal perspective, the handbook treats affixation (prefixation, suffixation, infixation, circumfixation, etc.), conversion, reduplication, root and pattern and other templatic processes, as well as prosodic and subtractive means of forming new words. From a semantic perspective, it looks at the processes that form various types of adjectives, adverbs, nouns, and verbs, as well as evaluatives and the rarer processes that form function words. The book also surveys derivation in fifteen language families that are widely dispersed in terms of both geographical location and typological characteristics.

Linguistic Variation and Change

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Author: Scott F Kiesling

Publisher: Edinburgh University Press

ISBN: 0748688315

Category: Language Arts & Disciplines

Page: 208

View: 8470

A comprehensive study of variation and change, including current debates in the area.

Anglistische Korpuslinguistik

eine Einführung

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Author: Joybrato Mukherjee

Publisher: N.A

ISBN: N.A

Category: Computational linguistics

Page: 223

View: 8187

A Handbook of Statistical Analyses Using R

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Author: Torsten Hothorn,Brian S. Everitt

Publisher: CRC Press

ISBN: 9781420010657

Category: Mathematics

Page: 304

View: 323

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

Wörter und Regeln

die Natur der Sprache

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Author: Steven Pinker

Publisher: N.A

ISBN: 9783938478592

Category:

Page: 478

View: 606

Language

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Author: George Melville Bolling,Bernard Bloch

Publisher: N.A

ISBN: N.A

Category: Comparative linguistics

Page: N.A

View: 1132

Grammatik im Lexikon

Adjektiv-Nomen-Verbindungen im Deutschen und Niederländischen

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Author: Barbara Schlücker

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110394618

Category: Language Arts & Disciplines

Page: 322

View: 9546

Das ungeklärte Verhältnis zwischen Wortbildung und Lexikon ist Gegenstand einer umfassenden und lang andauernden Diskussion in der morphologischen bzw. grammatiktheoretischen Literatur. Gleiches gilt auch für die Frage nach der Abgrenzung zwischen Morphologie und Syntax. Eine zentrale Rolle innerhalb dieser Debatten spielen nominale Komposita. Der Band untersucht solche Komposita und korrespondierende phrasale bzw. phraseologische Einheiten und diskutiert sie in Hinblick auf das Verhältnis von Wortbildung, Syntax und Lexikon. Konkreter Untersuchungsgegenstand sind Adjektiv-Nomen-Komposita (z.B. Sauerkirsche), ein in der Literatur verhältnismäßig selten berücksichtigter Subtyp der nominalen Komposition, sowie Adjektiv-Nomen-Phraseologismen (z.B. saure Sahne) im Deutschen und im deutsch-niederländischen Sprachvergleich. Die Arbeit behandelt die morphosyntaktischen Eigenschaften dieser Verbindungen im Rahmen eines konstruktionsgrammatischen Ansatzes und schlägt eine detaillierte semantische Analyse vor. Dabei werden auch aktuelle Veränderungstendenzen berücksichtigt. Besondere Aufmerksamkeit gilt der Frage nach dem Verhältnis dieser Verbindungen zueinander und ihrer Repräsentation im mentalen Lexikon.

Modeling Techniques in Predictive Analytics with Python and R

A Guide to Data Science

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Author: Thomas W. Miller

Publisher: FT Press

ISBN: 013389214X

Category: Computers

Page: 448

View: 8116

Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each 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. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business 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 code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to 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

Meeting Handbook

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Author: Linguistic Society of America,Monica Ann Macaulay

Publisher: N.A

ISBN: 9781574732283

Category: Linguistics

Page: 143

View: 6552

Surviving Linguistics offers linguistics students clear, practical, and focused advice on how to succeed in graduate school and earn a degree. The book is a valuable resource for students at any stage of their graduate career, from learning to write linguistics papers through completing their dissertation and finding a job. Along the way, the author explains the process of submitting conference abstracts, presenting papers at conferences, publishing journal articles, writing grant applications, creating a CV, and much more. Throughout Surviving Linguistics, Macaulay emphasizes the importance of working with advisors, dissertation committees, and fellow graduate students. The book includes exercises, helpful references to numerous books and on-line resources, and an index.

Word Frequency Distributions

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Author: R. Harald Baayen

Publisher: Springer Science & Business Media

ISBN: 9781402009273

Category: Computers

Page: 335

View: 2293

This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics. Word frequency distributions are characterized by very large numbers of rare words. This property leads to strange phenomena such as mean frequencies that systematically change as the number of observations is increased, relative frequencies that even in large samples are not fully reliable estimators of population probabilities, and model parameters that vary with text or corpus size. Special statistical techniques for the analysis of distributions with large numbers of rare events can be found in various technical journals. The aim of this book is to make these techniques more accessible for non-specialists, both theoretically, by means of a careful introduction to the underlying probabilistic and statistical concepts, and practically, by providing a program library implementing the main models for word frequency distributions.

Modeling Techniques in Predictive Analytics

Business Problems and Solutions with R, Revised and Expanded Edition

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Author: Thomas W. Miller

Publisher: FT Press

ISBN: 0133886190

Category: Computers

Page: 384

View: 6934

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

R in a Nutshell

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Author: Joseph Adler

Publisher: O'Reilly Germany

ISBN: 3897216507

Category: Computers

Page: 768

View: 6993

Wozu sollte man R lernen? Da gibt es viele Gründe: Weil man damit natürlich ganz andere Möglichkeiten hat als mit einer Tabellenkalkulation wie Excel, aber auch mehr Spielraum als mit gängiger Statistiksoftware wie SPSS und SAS. Anders als bei diesen Programmen hat man nämlich direkten Zugriff auf dieselbe, vollwertige Programmiersprache, mit der die fertigen Analyse- und Visualisierungsmethoden realisiert sind – so lassen sich nahtlos eigene Algorithmen integrieren und komplexe Arbeitsabläufe realisieren. Und nicht zuletzt, weil R offen gegenüber beliebigen Datenquellen ist, von der einfachen Textdatei über binäre Fremdformate bis hin zu den ganz großen relationalen Datenbanken. Zudem ist R Open Source und erobert momentan von der universitären Welt aus die professionelle Statistik. R kann viel. Und Sie können viel mit R machen – wenn Sie wissen, wie es geht. Willkommen in der R-Welt: Installieren Sie R und stöbern Sie in Ihrem gut bestückten Werkzeugkasten: Sie haben eine Konsole und eine grafische Benutzeroberfläche, unzählige vordefinierte Analyse- und Visualisierungsoperationen – und Pakete, Pakete, Pakete. Für quasi jeden statistischen Anwendungsbereich können Sie sich aus dem reichen Schatz der R-Community bedienen. Sprechen Sie R! Sie müssen Syntax und Grammatik von R nicht lernen – wie im Auslandsurlaub kommen Sie auch hier gut mit ein paar aufgeschnappten Brocken aus. Aber es lohnt sich: Wenn Sie wissen, was es mit R-Objekten auf sich hat, wie Sie eigene Funktionen schreiben und Ihre eigenen Pakete schnüren, sind Sie bei der Analyse Ihrer Daten noch flexibler und effektiver. Datenanalyse und Statistik in der Praxis: Anhand unzähliger Beispiele aus Medizin, Wirtschaft, Sport und Bioinformatik lernen Sie, wie Sie Daten aufbereiten, mithilfe der Grafikfunktionen des lattice-Pakets darstellen, statistische Tests durchführen und Modelle anpassen. Danach werden Ihnen Ihre Daten nichts mehr verheimlichen.