General statistical methods (STA903)
Depending on the composition of the PhD student group, the following topics may be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, s elected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.
Course description for study year 2022-2023
Facts
Course code
STA903
Version
1
Credits (ECTS)
10
Semester tution start
Spring, Autumn
Number of semesters
1
Exam semester
Spring, Autumn
Language of instruction
English, Norwegian
Content
Depending on the composition of the PhD student group, the following topics may be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, s elected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.
Learning outcome
After completing the course, the student should have acquired knowledge regarding central concepts and ideas within advanced statistical theory and applications of such theory. The student should be able to apply such knowledge to understand advanced statistical texts and as a tool in their own research.
Required prerequisite knowledge
None
Recommended prerequisites
A masters degree in statistics, or a related subject which includes a variety of statistics courses.
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Oral exam | 1/1 | Passed / Not Passed |
Course teacher(s)
Course teacher:
Tore Selland KleppeCourse teacher:
Jörn SchulzCourse teacher:
Jan Terje KvaløyCourse coordinator:
Jan Terje KvaløyHead of Department:
Bjørn Henrik AuestadMethod of work
Lectures and guided self-study.