course-details-portlet

TMA4265

Stochastic Processes

Choose study year
Credits 7.5
Level Third-year courses, level III
Course start Autumn 2016
Duration 1 semester
Language of instruction English and norwegian
Examination arrangement Portfolio assessment

About

About the course

Course content

Markov processes with discrete/continuous time-parameter and discrete/continuous state space,
including branching processes, Poisson processes, birth and death processes, and Brownian
motion. Queueing processes. Procedures for simulation of stochastic processes.

Learning outcome

1. Knowledge. The student has basic knowledge about stochastic processes in the time domain. The student has acquired more detailed knowledge about Markov processes with a
discrete state state space, including Markov chains, Poisson processes and birth and death
processes. The student also knows about queueing systems and Brownian motion, in addition to mastering the fundamental principles of simulation of stochastic processes and the
construction of Markov chain Monte Carlo (MCMC) algorithms.
2. Skills. The student is able to formulate simple stochastic process models in the time domain
and provide qualitative and quantitative analyses of such models.

Learning methods and activities

Lectures, exercises and works (projects). Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination (80%) and works (projects) (20%). The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination.
The lectures may be given in English.

Compulsory assignments

  • Work

Course materials

Will be announced at the start of the semester.

Credit reductions

Course code Reduction From
SIF5072 7.5 sp
ST2101 7.5 sp
This course has academic overlap with the courses in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject areas

  • Statistics
  • Technological subjects

Contact information

Course coordinator

Department with academic responsibility

Department of Mathematical Sciences