LLING2240 - Multivariate statistics for linguistics

Access to this course is restricted to students who have already successfully completed an introductory statistics course, e.g. LFIAL2260.  
The course will cover the following topics:  

• Concept and structure of a statistical model (linear or non-linear) and examples of typical linguistic research questions 
• Regression models: introduction to different regression models (e.g. linear regression, logistic regression, etc.), algorithms to select variables, notion of multicollinearity, models’ estimation, interpretation of parameters, quality of predictions 
• Analysis of variance: presentation of different analysis of variance techniques (for parametric and non-parametric data; for independent or repeated measures; with one or two classification criteria, etc.), the logic of F-test, multiple comparison of means (post-hoc tests) 
• Linear mixed models: notion of generalised linear model, random effects, hierarchical models  
• Exploratory methods: exploration of linguistic data with methods such as principal component analysis, factor analysis, etc. 
• Classification methods: introduction to classification models, e.g. decision trees   
• Model validation: measures of goodness of fit, residual analysis, variance and sphericity homogeneity tests, detection of outliers or influential points, variable transformation, etc.