Geometric Data Analysis in Educational Research, 7.5 credits
Geometric data analysis (GDA) is a comprehensive set of methods for multivariate statistics, the most important of which are correspondence analysis (CA), multiple correspondence analysis (MCA), principal component analysis (PCA), and Euclidean classification.
The methods present data sets as clouds of points in multidimensional Euclidean spaces. The course aims to provide a general introduction to the mathematical foundations of geometric data analysis, an understanding of how these methods can be applied in social science and educational science studies, as well as practical knowledge of how geometric data analysis is carried out. The software SPAD and R are used.
Entry requirements
Knowledge equivalent to the learning goals in QRMs course Basic statistics for educational research (QRM1800) and Introduction to quantitative methods in educational research (QRM1810).
Course code
QRM2300
Application period
Fall 2024: 2024-04-01 - 2024-06-02