General statistical methods (STA903)
Depending on the composition of the PhD candidate group, the following topics will be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, selected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.
Course description for study year 2024-2025. Please note that changes may occur.
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 candidate group, the following topics will be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, selected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.
Learning outcome
After completing the course, the candidate should have acquired knowledge regarding central concepts and ideas within advanced statistical theory and applications of such theory. The candidate 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 master's 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 coordinator:
Tore Selland KleppeCourse teacher:
Jan Terje KvaløyCourse coordinator:
Jan Terje KvaløyHead of Department:
Bjørn Henrik AuestadMethod of work
Lectures and guided self-study.
Open for
Course assessment
There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.