On completion of the course, the student should be able to:
explain the principles of optimal estimation;
explain the theory of optimal tests, especially unbiased and invariant tests;
give an account of the decision theory;
explain the principles of the asymptotic behaviour of statistical methods, especially the asymptotic efficiency;
use the delta method, including the functional delta method;
explain the use of projection in statistics especially in linear regression and variance analysis.
Maximum likelihood-estimator, James Stein-estimator, M-estimators, optimality of the F-test, minimax tests, asymptotic efficiency, LAN-model, U-statistics, Hajek projection, linear models.
Lectures and problem solving sessions.
Written examination (8 credits points) at the end of the course as well as assignments (2 credit points) in accordance with instructions at course start.
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.