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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.

Programming --- Mathematical linguistics --- Mathematical statistics --- Linguistics --- R (Computer program language) --- Linguistique --- R (Langage de programmation) --- Statistical methods --- Méthodes statistiques --- Computational linguistics. --- Computational logistics. --- Linguistics -- Statistical methods. --- R (Computer program language). --- Languages & Literatures --- Philology & Linguistics --- #KVHA:Methodologie --- #KVHA:Statistiek --- #KVHA:Taalkunde --- Computerlinguïstiek --- Linguïstiek --- R (programmeertaal) --- Statistical methods. --- statistische methoden --- Computerlinguïstiek. --- R (programmeertaal). --- statistische methoden. --- Méthodes statistiques --- GNU-S (Computer program language) --- Language and languages --- Linguistics, Statistical --- Statistical linguistics --- Domain-specific programming languages --- Linguistics - Statistical methods --- Corpus Linguistics. --- Linguistic Data. --- Statistic Analysis.

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This book is the revised and extended second edition of Statistics for Linguistics with R. 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, and a revision of overview sections on statistical tests and regression modeling. The main revision is 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.The revisions are completed by a new visual tool to identify the right statistical test for a given problem and data set.

Programming --- Mathematical linguistics --- Mathematical statistics --- Linguistics --- R (Computer program language) --- Statistical methods. --- Statistiek --- Linguïstiek --- statistische methoden --- statistische methodes --- Statistiek. --- R (Computer program language). --- statistische methoden. --- statistische methodes. --- Statistical methods --- Statistische methoden. --- Statistische methodes. --- GNU-S (Computer program language) --- Domain-specific programming languages --- Language and languages --- Linguistics, Statistical --- Statistical linguistics --- Linguistics - Statistical methods

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This series of lectures provides an overview of the author's work on quantitative applications in cognitive linguistics by discussing a wide range of studies involving corpus-linguistic as well as experimental work. After a discussion of how corpus linguistics, cognitive linguistics, and psycholinguistics relate to each other, the author discusses empirical and statistical studies of a wide variety of phenomena including morphophonology (morphological blends and alliteration effects), corpus-based cognitive semantics, frequency and association at the syntax-lexis interface. The book concludes with chapters exemplifying the role that bottom-up approaches can take, the role of statistical methods more generally, and the role of converging evidence from corpus and experimental data.The lectures for this book were given at the 'The China International Forum on Cognitive Linguistics' in May 2013.

Pragmatics --- Psycholinguistics --- Mathematical linguistics --- Cognitive grammar --- Corpora (Linguistics) --- Computational linguistics --- Corpus-based analysis (Linguistics) --- Corpus linguistics --- Linguistic analysis (Linguistics) --- Language, Psychology of --- Language and languages --- Psychology of language --- Speech --- Linguistics --- Psychology --- Thought and thinking --- Automatic language processing --- Language data processing --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Multilingual computing --- Cognitive linguistics --- Grammar, Comparative and general --- Data processing --- Psychological aspects --- Data processing. --- Cognitive grammar.

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"In this book, Stefan Th. Gries provides an overview on how quantitative corpus methods can provide insights to cognitive/usage-based linguistics and selected psycholinguistic questions. Topics include the corpus linguistics in general, its most important methodological tools, its statistical nature, and the relation of all these topics to past and current usage-based theorizing. Central notions discussed in detail include frequency, dispersion, context, and others in a variety of applications and case studies; four practice sessions offer short introductions of how to compute various corpus statistics with the open source programming language and environment R"--

Corpora (Linguistics). --- Linguistic analysis (Linguistics). --- Psycholinguistics. --- Corpora (Linguistics) --- Linguistic analysis (Linguistics) --- Psycholinguistics

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This is the third, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters ? one on mixed-effects modeling, one on classification and regression trees as well as random forests ? plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials.

LANGUAGE ARTS & DISCIPLINES / Linguistics / General. --- Linguistics. --- R. --- Regression Modeling. --- Statistics. --- Linguistics --- Statistical methods. --- Language and languages --- Linguistics, Statistical --- Statistical linguistics --- Mathematical linguistics --- Statistical methods --- Linguistique. --- Statistique. --- Linguistics - Statistical methods --- R (Computer program language)