In most experimental situations one measures several dependent variables. When studying the variables one at a time, one usually does not get a complete picture of the experimental results. For this reason, in recent years, multivariate methods, in which the variables are studied simultaneously have become increasingly popular. This course covers both the underlying theory required to understand the multivariate methods, as well as their applications in data analysis. Some of the methods/models covered in the course are principal component analysis, factor analysis, discriminant analysis, multivariate analysis of variance (MANOVA), PLS, cluster analysis and multivariate analysis of repeated measurements. The course includes computer labs where multivariate data analysis is performed using statistical software.
In a degree, this course may not be included together with another course with a similar content. If unsure, students should ask the Director of Studies in Mathematics and Mathematical Statistics. The course can also be included in the subject area of computational science and engineering.
The course requires 90 ECTS including courses in Mathematical Statistics, minimum 15 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. Proficiency in English equivalent to Swedish upper secondary course English A/5. Where the language of instruction is Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.