Entry requirements

Probability Theory II.

Learning outcomes

In order to pass 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. Written assignments that may be included as a part of the written examination can occur during the course according to instructions that are delivered at course start.

Other directives

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