The course provides the basic theory and methods for multivariate data analysis and lays a solid foundation for learning more advanced methods and algorithms in the next step. It starts from multivariate Gaussian distribution (MGD) and its generalization, the Gaussian mixture model. The maximum likelihood estimation (MLE) and the EM algorithm are discussed. Based on MGD, statistical inference approaches (Hotelling's T square test, multivariate analysis of variance, MANOVA), classification methods (Linear discriminant analysis and logistic regression), and clustering analysis methods are covered. Furthermore, based on the projection ideas, different eigen-decomposition based methods for dimensionality reduction, such as principal component analysis (PCA), factor analysis (FA), canonical correlation analysis (CCA), and partial least squares (PLS) are introduced. Models for regression analysis with colinear explanatory variables such as principal component regression (PCR) and PLS regression are also included.
The course requires 90 ECTS including courses in Mathematical Statistics, minimum 12 ECTS, or courses in Statistics, minimum 75 ECTS and in both cases a course in Basic Calculus, 7,5 ECTC and a course in Linear algebra, 7,5 ECTS, or equivalent. Proficiency in English and Swedish equivalent to the level required for basic eligibility for higher studies.
Guaranteed place
Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.
Application code
UMU-58207
Application
Application deadline was
15 April 2024.
The application period is closed.
Application and tuition fees
As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.
