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 information below is only for exchange students
Starts
28 August 2023
Ends
30 October 2023
Study location
Umeå
Language
English
Type of studies
Daytime,
50%
Required Knowledge
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.
Selection
Students applying for courses within a double degree exchange agreement, within the departments own agreements will be given first priority. Then will - in turn - candidates within the departments own agreements, faculty agreements, central exchange agreements and other departmental agreements be selected.
Application code
UMU-A5829
Application
This application round is only intended for nominated exchange students. Information about deadlines can be found in the e-mail instruction that nominated students receive.
The application period is closed.
