Content and learning outcomes
The course intends to give a basic introduction to mathematical models and modeling uncertainty. Various types of models are treated and validated. Different kinds of uncertainties are highlighted. The course treats modeling within a number of subject areas and covers amongst others uncertainty in input data, model parameters and model structures, as well as hypothesis testing under uncertainty. The course further treats stochastic and deterministic simulation as well as various types of networks, including neural networks. Applications to different subject areas will be analysed.
Intended learning outcomes
After completion of the course, the student should:
- understand what it implies to model a phenomenon and be able to explain various types of models.
- be able to explain different techniques to evaluate models.
- understand and estimate the uncertainty in chosen models.
- with chosen models test appropriate hypotheses.
Literature and preparations
Completion of basic higher education.
Fastställs i överenskommelse med de studerande beroende på deras intresseområde.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
Examination 3.0 Credits
Written assignment 4.5 Credits
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.