Swedish name: Stokastiska processer och simulering
This syllabus is valid: 2022-07-25
and until further notice
Course code: 5MS049
Credit points: 7.5
Education level: First cycle
Main Field of Study and progress level:
Mathematical Statistics: First cycle, has less than 60 credits in first-cycle course/s as entry requirements
Mathematics: First cycle, has less than 60 credits in first-cycle course/s as entry requirements
Grading scale: Pass with distinction, Pass with merit, Pass, Pass with distinction, Pass, Fail
Established by: Faculty Board of Science and Technology, 2015-06-11
Revised by: Faculty Board of Science and Technology, 2023-03-09
Contents
Moment 1 (4.0 hp): Theory. Moment covers the basic theory of stochastic processes theory of stochastic simulation (Monte Carlo methods). The course covers the generation of random numbers from different continuous and discrete distributions and integral estimation including error estimation. Further, theory and methods for simulating random walks, Brownian motion, Poisson processes and Markov chains are introduced together with their real life applications.
Moment 2 (3.5 hp): Computer labs. Application of the introduced computer intensive methods using suitable programming language. Additionally the simulation of queuing and production lines and inventory systems based on the discrete events approach is introduced.
Expected learning outcomes
Expected learning outcomes
Determine algorithms for simulating random numbers from the discrete and continuous distributions
Use simulatioons to estimate integrals and properties of random variables together with corresponding measures of accuracy
Calculate analytically the properties of random walk, Brownian motion, Poisson process and Markov Chains
With help of computer software, simulate the realisations of the stochastic processes introduced in the course and use them to estimate properties of the underlying random processes
Construct simple discrete event based systems and analyse their output
Present the results of the analysis in oral and written form.
Required Knowledge
The course requires 15 ECTS mathematics, 6 ECTS mathematical statistics and 7.5 ECTS computer programming, or equivalent.
Form of instruction
Lectures, classes and computer labs
Examination modes
Written examination on moment 1 (U/3,4,5) Written lab reports and oral presentation on moment 2 (U/G)
Literature
Valid from:
2022 week 30
Material tillhandahålles av inst. Institutionen för matematik och matematisk statistik :
