Stochastic Modelling
Syllabus, Bachelor's level, 1MS007
This course has been discontinued.
- Code
- 1MS007
- Education cycle
- First cycle
- Main field(s) of study and in-depth level
- Mathematics G1F, Sociotechnical Systems G1F
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 15 March 2007
- Responsible department
- Department of Mathematics
Entry requirements
Probability and Statistics
Learning outcomes
In order to pass the course (grade 3) the student should be able to
Higher grades, 4 or 5, require a higher level of proficiency. The student should be able to treat and solve problems of greater complexity, i.e. problems requiring a combination of ideas and methods for their solution, and be able to give a more detailed account of the proofs of important theorems and by examples and counter-examples be able to motivate the scope of various results.
Requirements concerning the student's ability to present arguments and reasoning are greater.
Content
Stochastic processes, the Poisson process, life length models. Stochastic simulation. Markov chains in discrete and continuous time. Stationary and asymptotic distribution. Absorption probability, absorption time. Selected examples of applications of stochastic modelling, depending on study programme.
Instruction
Lectures and problem solving sessions.
Assessment
Written examination at the end of the course. Moreover, compulsory assignments may be given during the course.