Entry requirements

60 credits including 20 credits in mathematics. Participation in Probability Theory II and Inference Theory I.

Learning outcomes

On completion of the course, the student should be able to

• describe the idea of statistical modelling;
• understand the inference principles;
• apply several methods for parameter estimation;
• describe the methods and their theoretical properties and practical applicability;
• describe the theoretical basis for hypothesis testing;
• perform testing of hypotheses in several variants.

Content

Inference principles: statistical models, exponential families, inference based on likelihood, Fisher information and sufficiency, estimation methods, Cramér-Rao inequality, optimality, hypothesis testing, Neyman Pearson tests, uniformly most powerful tests.

Instruction

Lectures and problem solving sessions.

Assessment

Written examination at the end of the course (4 credits). Written assignments (1 credit).

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.

Other directives

The course may not be included in higher education qualification together with Mathematical Statistics (1MS013) 15 credits.