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Levshina N. How to do Linguistics with R: Data exploration and statistical analysis

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Levshina N. How to do Linguistics with R: Data exploration and statistical analysis
Amsterdam: John Benjamins Publishing Company, 2015. — 456 p. — ISBN 9027212252, 9789027212252.
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.
This book has a companion website: http://doi.org/10.1075/z.195.website
What is statistics? Main statistical notions and principles
Introduction to R
Descriptive statistics for quantitative variables
How to explore qualitative variables: Proportions and their visualizations
Comparing two groups: t-test and Wilcoxon and Mann-Whitney tests for independent and dependent samples
Relationships between two quantitative variables: Correlation analysis with elements of linear regression modelling
More on frequencies and reaction times: Linear regression
Finding diferences between several groups: Sign language, linguistic relativity and ANOVA
Measuring associations between two categorical variables: Conceptual metaphors and tests of independence
Association measures: Collocations and collostructions
Geographic variation of quite: Distinctive collexeme analysis
Probabilistic multifactorial grammar and lexicology: Binomial logistic regression
Multinomial (polytomous) logistic regression models of three and more near synonyms
Conditional inference trees and random forests
Behavioural proiles, distance metrics and cluster analysis
Introduction to Semantic Vector Spaces: Cosine as a measure of semantic similarity
Language and space: Dialects, maps and Multidimensional Scaling
Multidimensional analysis of register variation: Principal Components
Exemplars, categories, prototypes: Simple and multiple correspondence analysis
Constructional change and motion charts
The most important R objects and basic operations with them
Main plotting functions and graphical parameters in R
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