Høst 2022

STA-3002 Multivariable Statistical Analysis - 10 stp

The course is administrated by

Institutt for matematikk og statistikk

Type of course

The course is included in the study program Mathematical Sciences - master. It may be taken independent of study program upon approval of the Department of mathematics and statistics. This course is also available for inbound exchange students.

Course overlap

STA-8002 Multivariable Statistical Analysis 10 stp

Course contents

The course builds on STA-2002 Theoretical Statistics and gives a thorough introduction to the multivariate normal distribution, as well as estimation of its parameters and related inference. This includes simultaneous inference for mean vectors, testing of general linear hypotheses and multiple linear regression analysis. Further, the course covers topics like principal component analysis, factor analysis and classification methods.

Application deadline

Applicants from countries within EU/EEA: June 1st for the autumn semester and December 1st for the spring semester. Exchange students and Fulbright students: 1 October for the spring semester and 15 April for the autumn semester.

Admission requirements

Bachelor of science degree in statistics/mathematics or equal. Recommended prerequsites is STA-2002 Theoretical Statistics. Application code is 9371.

Objective of the course

The student shall

obtain a thorough introduction to the multivariate normal distribution, as well as estimation of its parameters.
obtain solid understanding of various areas in multivariable statistical analysis, such as the classification problem, testing of general linear hypotheses, principal component analysis, factor analysis and various regression techniques.
be able to use these concepts to solve specific problems.

Language of instruction

The language of instruction and the syllabus is English. Examination questions will be given in English, but may be answered either in English or a Scandinavian language.

Teaching methods

The course consists of 40 hours of lectures and 30 hours of coursework including submission of up to 4 mandatory assignments.