Skip to main content

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 Kleppe
Course teacher: Jörn Schulz
Course teacher: Jan Terje Kvaløy
Course coordinator: Jan Terje Kvaløy
Head of Department: Bjørn Henrik Auestad
Method of work
Lectures and guided self-study.
Open for
Technology and Natural Science - PhD programme
Literature
Search for literature in Leganto