| Skriv ut |  | Lukk vindu |
Høst 2023
STA-2002 Theoretical Statistics - 10 stp
The course is administrated by
Institutt for matematikk og statistikk
Type of course
The course is included in the study programs Applied Physics and Mathematics - master (5-years) and Mathematical Sciences - Bachelor. It may also be taken independent of study program. This course is also available for inbound exchange students.
Course overlap
S-201 Advanced statistics 10 ects
Course contents
This course builds on STA-1001 Statistics and probability with a thorough discussion of statistical methods and principles (sufficiency, power-optimality, exponential classes, maximum likelihood, Bayesian estimation).
Admission requirements
Applicants from Nordic countries: Generell studiekompetanse og følgende spesielle opptakskrav: Matematikk R1 + R2 og i tillegg enten:
- Fysikk 1 + 2 eller
- Kjemi 1+ 2 eller
- Biologi 1 + 2 eller
- Informasjonsteknologi 1 +2 eller
- Geofag 1 + 2 eller
- Teknologi og forskningslære 1 + 2
International applicants: Higher Education Entrance Qualification and certified language requirements in English. It is a requirement that students have some prior knowledge of biology and ecology, chemistry and mathematics (Participants must have taken introductory level university courses, and achieved pass grades, in these subjects).
A list of the requirements for the Higher Education Entrance Qualification in Norway can be found on the Norwegian Agency for Quality Assurance in Education website - nokut.no
Application code: 9336 (Nordic applicants).
Objective of the course
The candidate shall:
- obtain thorough knowledge and understanding of the statistical principles and concepts sufficiency, power-optimality, exponential classes, maximum likelihood, Bayesian estimation.
- be able to apply these concepts to solve problems.
Language of instruction
The language of instruction and the syllabus is English. Examination questions will be given in English, but may be answered either in English or a Scandinavian language.
Teaching methods
Lectures: Approx 40 h. Coursework: Approx 30 h.