Course
Statistical Modeling and Simulation (STA510)
This course provides a foundation for problem solving in technology, science and economy using statistical modeling, simulation and analysis.
Dette er emnebeskrivelsen for studieåret 2025-2026. Merk at det kan komme endringer.
Fakta
Emnekode
STA510
Vekting (stp)
10
Semester undervisningsstart
Autumn
Undervisningsspråk
English
Antall semestre
1
Vurderingssemester
Autumn
Timeplan
Litteratur
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.
Learning outcome
After completing 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
Forkunnskapskrav
Et av følgende alternativer:
Mathematical Methods 1 (MAT100)
Mathematical Methods 2 (MAT200)
Probability and Statistics 1 (STA100)
Mathematical Methods 1 (MAT100)
Mathematical Methods 2 (MAT200)
Probability and Statistics 1 (STA100)
Anbefalte forkunnskaper
Mathematical Methods 1 (MAT100), Mathematical Methods 2 (MAT200), Probability and Statistics 1 (STA100)
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Written exam | 1/1 | 4 Hours | Letter grades | Standard calculator |
Written exam is with pen and paper
Vilkår for å gå opp til eksamen/vurdering
Compulsory assignments
Two compulsory assignments must be approved in order to have access to the exam.
Fagperson(er)
Head of Department:
Bjørn Henrik AuestadCourse coordinator:
Tore Selland KleppeCourse teacher:
Jörn SchulzMethod of work
4 +2 hours of lectures and problem solving/data lab per week, self study
Åpent for
Admission to Single Courses at the Faculty of Science and Technology
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Computational Engineering - Master of Science Degree Programme
Computer Science - Master of Science Degree Programme
Environmental Engineering - Master of Science Degree Programme
Industrial Economics - Master of Science Degree Programme
Robot Technology and Signal Processing - Master's Degree Programme
Structural and Mechanical Engineering - Master of Science Degree Programme
Mathematics and Physics - Master of Science Degree Programme
Mathematics and Physics - Five Year Integrated Master's Degree Programme
Offshore Field Development Technology - Master of Science Degree Programme
Industrial Asset Management - Master of Science Degree Programme
Marine and Offshore Technology - Master of Science Degree Programme
Offshore Technology - Master's Degree Programme
Petroleum Geosciences Engineering - Master of Science Degree Programme
Petroleum Engineering - Master of Science Degree Programme
Master's Degree Programme in Societal Safety, Specialisation in Technical Social Safety
Risk Management - Master's Degree Programme (Master i teknologi/siviling.)
Exchange programme at Faculty of Science and Technology
Emneevaluering
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 course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.
The course description is retrieved from FS (Felles studentsystem). Version 1