| University of Stavanger

Facts

Course code

STA510

Credits (ECTS)

Semester tution start

Autumn

Number of semesters

Exam semester

Autumn

Language of instruction

English

Offered by

Faculty of Science and Technology, Department of Mathematics and Physics

Learning outcome

After taking this course the student will:

Knowledge

be able to make and use statistical models for a number of problems in technology, natural science and economics
have knowledge of the strengths and limitations of some key techniques for statistical modeling og simulation

Skills

be able to implement the models (in R)
carry out simulations of statistical models, analyze the results statistically, and
be able to make assessments of uncertainty in the results

General competence

be able to solve complicated problems using programming and computers
present results in a proper manner

Content

The course focuses on methods to model and analyze a variety of random phenomena. The analysis will in practice often be done by simulation, but also the theoretical analysis is important. Students shall be able to implement statistical models on a computer, generate, interpret and present results. Topics that are appropriate to address: the general statistical model building, assessing the goodness of the model, estimation of distribution and parameters of the model and assess the uncertainty of estimates, bootstrap, number generators, variance reduction techniques, modeling and simulation of dependencies, modeling and simulation of stochastic processes, basic Bayesian statistics and Markov chain Monte Carlo. The course will have several exercises with the use of computers and the program R.

Required prerequisite knowledge

None

Recommended prerequisites

MAT100 Mathematical Methods 1, MAT200 Mathematical Methods 2, STA100 Probability and Statistics 1

Exam

Form of assessment	Weight	Duration	Marks	Aid
Portfolio with 3 individual written assignments	1/1		A - F	All.

The first assignment counts 10%, the second assignment count 30% and the third assignment counts 60%. Course teacher sets final marks.Candidates who fail on the assignments will not be able to submit new project assignments until the next time the course is taught.

Course teacher(s)

Course coordinator: Tore Selland Kleppe

Course teacher: Stein Andreas Bethuelsen

Course coordinator: Tore Selland Kleppe

Head of Department: Bjørn Henrik Auestad

Method of work

Four hours of problem solving/data lab per week. Lectures on online videos

Open for

Course assessment

Usually by forms and/or discussion according to university regulations.

Overlapping courses

Course	Reduction (SP)
Statistic modelling and simulation (TE6039)	5
Statistical modelling and simulation (MET260)	10

Literature

Search for literature in Leganto

Statistical modeling and simulation STA510