Linear Statistical Models

Random vectors. Multivariate normal distribution. Multiple linear regression. Analysis of variance. Multiple hypothesis testing. Design of experiments.

1. Knowledge: The student has strong theoretical knowledge about the most popular statistical models and methods that are used in science and technology, with emphasis on regression-type statistical models. The statistical properties of the multivariate normal distribution are well known to the student, and the student is familiar with the role of the multivariate normal distribution within linear statistical models.

2. Skills: The student knows how to design an experiment and how to collect informative data of high quality to study a phenomenon of interest. Subsequently, the student is able to choose a suitable statistical model, apply sound statistical methods, and perform the analyses using statistical software. The student knows how to present the results from the statistical analyses, and how to draw conclusions about the phenomenon under study.

Lectures, exercises and a written exam.