Likelihood, sufficiency, consistency, ML-estimations. Most powerful and uniformly most powerful estimators, likelihood ratio test. Exponential families.
SF2960 Statistical Theory 6.0 credits
Information per course offering
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Course syllabus as PDF
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Course syllabus SF2960 (Autumn 2007–)Content and learning outcomes
Course contents
Intended learning outcomes
To pass the course, the student should be able to do the following:
- define concepts and derive results in statistical inference theory
- determine if a statistical model is suitable for a particular statistical problem
- perform statistical analysis on real data, and
- critically examine and analyse the correctness and reasonability of calculated results.
To receive the highest grade, the student should in addition be able to do the following:
- Combine all the concepts and methods mentioned above in order to solve more complex problems.
Literature and preparations
Specific prerequisites
SF1906 (5B1506) Mathematical statistics, basic course, SF2940 (5B1540) Probability theory or equivalent courses.
Recommended prerequisites
Equipment
Literature
Lindgren, B.W. Statistical theory. The MacMillan Company. (The book may be changed by another book.) Material from the Department of Mathematics at the Stockholm University.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- TEN1 - Examination, 6.0 credits, grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
A written examination.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.