analyzing linguistic data a practical introduction to statistics using r

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Analyzing Linguistic Data

Author : R. H. Baayen
ISBN : 9781139470735
Genre : Language Arts & Disciplines
File Size : 33. 46 MB
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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.

Advancing Quantitative Methods In Second Language Research

Author : Luke Plonsky
ISBN : 9781317974086
Genre : Language Arts & Disciplines
File Size : 75. 71 MB
Format : PDF, Kindle
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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

The Oxford Handbook Of Laboratory Phonology

Author : Abigail C. Cohn
ISBN : 9780199575039
Genre : Language Arts & Disciplines
File Size : 21. 63 MB
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This book provides state-of-the-art coverage of research in laboratory phonology. Laboratory phonology denotes a research perspective, not a specific theory: it represents a broad community of scholars dedicated to bringing interdisciplinary experimental approaches and methods to bear on how spoken language is structured, learned and used; it draws on a wide range of tools and concepts from cognitive and natural sciences. This book describes the investigative approaches,disciplinary perspectives, and methods deployed in laboratory phonology, and highlights the most promising areas of current research.Part one introduces the history, nature, and aims of laboratory phonology. The remaining four parts cover central issues in research done within this perspective, as well as methodological resources used for investigating these issues. Contributions to this volume address how laboratory phonology approaches have provided insight into human speech and language structure and how theoretical questions and methodologies are intertwined. This Handbook, the first specifically dedicated tothe laboratory phonology approach, builds on the foundation of knowledge amassed in linguistics, speech research and allied disciplines. With the varied interdisciplinary contributions collected, the Handbook advances work in this vibrant field.

Automatic Treatment And Analysis Of Learner Corpus Data

Author : Ana Díaz-Negrillo
ISBN : 9789027270955
Genre : Language Arts & Disciplines
File Size : 79. 56 MB
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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).

Experimental Research Methods In Sociolinguistics

Author : Katie Drager
ISBN : 9781474251792
Genre : Language Arts & Disciplines
File Size : 49. 40 MB
Format : PDF
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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

Text Analysis With R For Students Of Literature

Author : Matthew Jockers
ISBN : 9783319031644
Genre : Computers
File Size : 24. 39 MB
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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.

Linguistic Variation And Change

Author : Scott F Kiesling
ISBN : 9780748688319
Genre : Language Arts & Disciplines
File Size : 64. 24 MB
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A comprehensive study of variation and change, including current debates in the area.

The Oxford Handbook Of Derivational Morphology

Author : Rochelle Lieber
ISBN : 9780191651786
Genre : Language Arts & Disciplines
File Size : 64. 48 MB
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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.

A Handbook Of Statistical Analyses Using R

Author : Torsten Hothorn
ISBN : 1420010654
Genre : Mathematics
File Size : 44. 91 MB
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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.

Modeling Techniques In Predictive Analytics With Python And R

Author : Thomas W. Miller
ISBN : 9780133892147
Genre : Computers
File Size : 72. 35 MB
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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

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