Stochastic Data Processing and Simulation

The course is part of the Bachelor Program in Mathematical Sciences ("Matematikprogrammet") but it is also open for students outside the program who meet the course prerequisites.

The course can be part of the following programmes: 1) Mathematical Sciences, Master's Programme (N2MAT), 2) Bachelor's Programme in Mathematics ("Matematikprogrammet", N1MAT) and 3) Complex Adaptive Systems, Master's Programme (N2CAS).

Knowledge equivalent to an introductory course in probability theory and basic mathematical statistics is required. Prior experience of using a high-level programming language for technical or scientific computation is also required.

The course covers computational and analytical work in stochastic modelling, simulation, and statistical data processing within mathematical statistics and its applications. The content includes work with probabilistic models, simulation techniques, and statistical methods, with emphasis on the relationship between theory, computation, and interpretation of results.

After completion of the course, the student should be able to:

• Apply fundamental concepts from probability theory and mathematical statistics in the analysis of stochastic models relevant to data processing and simulation.
• Implement statistical and stochastic methods to carry out simulations and data analyses.
• Interpret and assess numerical results in relation to underlying mathematical assumptions.
• Combine analytical reasoning and computational approaches in the solution of statistical problems.
• Document and communicate mathematical and statistical work clearly and coherently in written form using appropriate mathematical notation.

Teaching may include lectures, computer-based teaching activities, and supervised work.

Written and oral examination based on project work.

If a student who has failed the same examined component twice wishes to change examiner before the next examination, a written application shall be sent to the department responsible for the course and shall be granted unless there are special reasons to the contrary (Chapter 6, Section 22 of the Higher Education Ordinance).

The grading scale comprises: Pass with Distinction (VG), Pass (G) and Fail (U).

At the end of the course the students will be asked to answer a course evaluation questionnaire. The results from the evaluation and potential changes to the course will be shared with students who participated in the evaluation and students who are starting the course.