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Stochastic Processes and Simulation I

In this course you will learn about stochastic processes, which are functions that develop over time in a partially random way. Note that this course is often given in Swedish.

You can find the Swedish version of this page here

A stochastic process means a function that develops itself over time in a partially random way, like, for example, the weather, the price of a share or the amount of waiting patients at a doctor's. We will study some important mathematical models for such functions, using both probability theory, and computer simulations.

To be eligible for the course, you must have knowledge equivalent to the course Probability Theory I.

Course content

The course covers conditional distribution and conditional expectation, Markov chains in discrete and continuous time, birth and death processes, the Poisson process and basic stochastical simulation.

  • Course structure

    The course consists of two elements, a theory part with a written examination, and computer exercises.

    Teaching format

    The education consists of lectures, exercises, and computer exercises. The course usually has two lectures a week, followed by an exercise session.


    The theory part of the course, worth 6 credits, is assessed through a written examination, the grade is on a scale A-F. The computer exercises, worth 1.5 credits, are assessed though written reports handed in during the course. For more details, see the course page.

    To pass the course you must pass both these parts. The final grade is decided by the grade on the written exam.


    A list of examiners can be found on

    Exam information

  • Schedule

    The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
  • Course literature

    Note that the course literature can be changed up to two months before the start of the course.

    Ross: Introduction to probability models. Academic Press.

    List of course literature Department of Mathematics

  • More information

    New student
    During your studies

    Course web

    We do not use Athena, you can find our course webpages on

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