This book provides a linguist with a statistical toolkit for exploration and analysis of linguistic data. It employs R, a free software environment for statistical computing, which is increasingly popular among linguists. How to do Linguistics with R: Data exploration and statistical analysis is unique in its scope, as it covers a wide range of classical and cutting-edge statistical methods, including different flavours of regression analysis and ANOVA, random forests and conditional inference trees, as well as specific linguistic approaches, among which are Behavioural Profiles, Vector Space Models and various measures of association between words and constructions. The statistical topics are presented comprehensively, but without too much technical detail, and illustrated with linguistic case studies that answer non-trivial research questions. The book also demonstrates how to visualize linguistic data with the help of attractive informative graphs, including the popular ggplot2 system and Google visualization tools.
“Levshina’s book achieves something few other books on doing linguistics with R have achieved. She has written a book that makes sense even for novice users of R and for linguists not accustomed to statistical computing. Levshina writes in a pedagogically sensitive style, in friendly language, and with just the right amount of explanatory prose to lead the reader to insightful analyses. Taken together, the chapters introduce the reader to a sparkling variety of statistical methods. Best of all, from the point of view of linguists, real *linguistic *problems take centre stage throughout the book– the statistical methods are the means to answer intriguing linguistic questions, not an end in themselves.”
John Newman, University of Alberta
“This is a fantastic textbook: extremely comprehensive (the book surveys almost all major analysis technique used in the linguistic literature – from descriptive statistics over regression analysis to semantic vector space modeling), well-written, and with a much appreciated emphasis on good data visualization. Both beginning and more experienced quantitative linguists will find this book an invaluable resource.”
Benedikt Szmrecsanyi, University of Leuven
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