How to do Linguistics with R : data exploration and statistical analysis / Natalia Levshina

What is statistics? Main statistical notions and principles. -- Introduction to R. -- Descriptive statistics for quiatitative variables. -- How to explore qualitative variables: Proportions and their visualizations. -- Compraring two groups: t-test and Wilcoxon and Mann-Whitney test for independent and dependent samples. -- Raltionships between two quantitative variables: Correlation analysis with elements of linear regression modelling. -- More on frequencies and reaction times: Linear regression. -- Finding differences between several groups: Sign language, lingusitic relativity and ANOVA. -- Measuring associations between two categorical variables: Conceptual metaphors and tets of independence. -- Association measures: Collocations and collostructions. -- Geographic variation of quite: Distinctive collexeme analysis. -- Probabilistic multifactorial grammar and lexicology: Binomial logistic regression. -- Multinominal (polytomous) logistic regression models of three and more near synonyms. -- Conditional interference trees and random forests. -- Behavioural profiles, 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. -- Multimensional analysis of register variation: Principal Componenets Analysis of register variation: Principal Components Analysis and Factor Analysis. -- Exeplars, categories, prototypes: Simple and multiple correspondence analysis. -- Constructional change and motion charts.

Lenguaje y lenguas