Statistical Modeling and Simulation (STA510)
This course provides a foundation for problem solving in technology, science and economy using statistical modeling, simulation and analysis.
Course description for study year 2025-2026
Facts
Course code
STA510
Version
1
Credits (ECTS)
10
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
Time table
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
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 |
|---|---|---|---|---|
| Written exam | 1/1 | 4 Hours | Letter grades | Standard calculator |
Written exam is with pen and paper
Coursework requirements
Compulsory assignments
Two compulsory assignments must be approved in order to have access to the exam.
Course teacher(s)
Course coordinator:
Jörn SchulzCourse teacher:
Jörn SchulzCourse teacher:
Jörn SchulzCourse teacher:
Jörn SchulzHead of Department:
Bjørn Henrik AuestadMethod of work
4 +2 hours of lectures and problem solving/data lab per week, self study
Overlapping courses
| Course | Reduction (SP) |
|---|---|
| Statistic modelling and simulation (TE6039_1) | 5 |
| Statistical modelling and simulation (MET260_1) | 10 |
Open for
Exchange programme at Faculty of Science and Technology
Admission requirements
Must meet the admission requirements of one of the study programmes the course is open for.
Course assessment
The faculty decides whether early dialogue should be conducted in all or selected groups of courses offered by the faculty. The purpose is to gather feedback from students for making changes and adjustments to the course during the current semester. In addition, a digital evaluation, students’ course evaluation, must be conducted at least once every three years. Its purpose is to collect students` experiences with the course.
