Theoretical Statistics DS

7.5 credits

Syllabus, Master's level, 1MS039

Code
1MS039
Education cycle
Second cycle
Main field(s) of study and in-depth level
Data Science A1N, Mathematics A1N
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 3 March 2022
Responsible department
Department of Mathematics

Entry requirements

120 credits including 90 credits in mathematics. Participation in Inference Theory II. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

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.

Content

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.

Instruction

Lectures and problem solving sessions.

Assessment

Written examination (5 credits) at the end of the course as well as assignments (2.5 credit) during the course.

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

This course cannot be included in the same degree as the course ​1MS033.

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