Analysing data in R

obligatory courses

Classroom

The aim of the course is to teach the basics of data analysis and visualisation using R Studio. During the class, we will go through some basic notions and commands, basic syntax and packages for writing scripts and then discuss the statistical notions learned at the two statistics courses during the first year. All the concepts will be illustrated with linguistic data. Students will learn how to visualise data results, how to create and interpret appropriate graphs and tables, and how to run basic statistics using the R environment.

Knowledge: the graduate knows and understands:

-in-depth, specialized terminology in the fields of theoretical linguistics, corpus linguistics, neuroscience

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

-the work environment as well as economic and legal conditions of work in the profession of a linguist, researcher, software tester, copy editor and copywriter

-the principles of creating various forms of entrepreneurship and the functioning of a linguist within the framework of various forms of entrepreneurship (freelance, translation bureaus, editorial team, research group, educational material preparation company, language technology development company, etc.) on the domestic and international markets

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

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

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