Advanced multivariate analysis

This course contributes to the Master's programme in Computational Social and Political Sciences by providing students with advanced methodological tools for the analysis of complex social and political data. The course introduces students to the logic of multivariate statistical reasoning and to modern approaches to quantitative data analysis used in computational social science.

The course integrates theoretical understanding of statistical models with hands-on computational practice using the R statistical environment. Particular attention is devoted to the interpretation of statistical results, the evaluation of model assumptions, and the development of reproducible research workflows.

Through applications to real-world datasets and simulation-based learning, the course equips students with the methodological foundations necessary to conduct independent empirical research and to critically assess quantitative evidence in academic, policy, and media contexts.

By the end of the course students will be able to:
- understand and apply multivariate statistical techniques commonly used in social and political science research;
- implement statistical analyses using the R programming language;
- critically evaluate the assumptions and limitations of statistical models;
- interpret and communicate statistical results in a clear and substantively meaningful way;
- design and implement an empirical research project using quantitative data;
- reproduce and document statistical analyses using transparent and replicable workflows.