On completion of the course, the student should be able to:
have acquired a profound insight into some delimited area of probability theory, statistics, or some applied area of mathematics;
have been introduced to some area of current mathematical statistical research and be able to independently acquire information about literature and problems in the area;
be able to prepare and hold a seminar presentation in some area of modern mathematical statistical research.
The contents of the course varies from one instance to another. Examples of themes: Asymptotic statistics, Brownian motion, Extreme value theory, Network and queuing theory, Risk analysis.
Lectures and seminars.
Assignments during the course. Presentation of a given subject at a seminar.
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.