Statistics for linguists – intermediate

obligatory courses

Classroom

The aim of this course is to provide the knowledge and practical applications of statistical analysis at an intermediate level. The course will review the assumptions and interpretation of parametric tests and linear regression analysis, teach how to conduct and interpret non-linear regressions (i.e., binomial, ordinal, and count outcome variables), and provide the basics of linear mixed-effects models. At the end of the course, earners will be able to deal with non-linear data, multilevel data, and will be able to conduct analysis on several variables in order to identify commonalities (e.g., factors) among the variables.

Knowledge: the graduate knows and understands:

-in-depth, the main directions of development and contemporary research trends in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and knows where the most important linguistic research centers in Europe and the world are located

-in-depth, research methods used in: psycholinguistics, neurolinguistics, corpus linguistics, digital linguistics and text linguistics, as well as statistical models

-in-depth, the relationship of linguistics (theoretical, computational, cognitive, corpus linguistics) with other fields of (neuro)science

Skills: the graduate is able to:

-use in-depth theoretical and practical knowledge to carry out research work and solve complex problems in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) using appropriate methodology

-to an in-depth degree, search, analyze, evaluate and select information in the native language and foreign languages

-use advanced research tools of linguistics (theoretical, computational, cognitive, corpus-based) and select research methods appropriately to the problems undertaken

-use in-depth knowledge of linguistics (theoretical, computational, cognitive, corpus-based, social/text linguistics) through the selection and appropriate application of modern information and communication technology (including statistical, corpus, eye-tracking and EEG analysis software) when working with research data

-use in-depth knowledge of research methodologies (acoustic analysis, eye-tracking, EEG, corpus analysis, data analysis: R, Python) used in modern linguistics to plan and carry out a methodologically correct scientific study, as well as to analyze its results and identify implications

-use a foreign language to an advanced degree (C2 level) in specialized terminology in the field of linguistics (theoretical, computational, cognitive, corpus, social/text linguistics)

-lead the work of a team in a linguistics project using advanced research methods and new technologies

-independently acquire knowledge in the field of linguistics (theoretical, computational, cognitive, corpus, social/text linguistics) and evaluate the usefulness of the learned methods, practices and procedures in their own professional activity

Social competences: the graduate is ready to:

-recognize the importance of the latest linguistic knowledge and critically evaluate research in linguistics (theoretical, computational, cognitive, corpus, social/text linguistics), especially those published in scientific journals and monographs and popular science sources

-recognize the importance of linguistic knowledge in solving cognitive and practical problems and to consult with experts

-initiate and carry out linguistic research, in particular to improve accessibility in the dimensions of language, information and communication