273023.0 Markov Chains (5 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
Contents of the course:
- the Markov property
- definition of a Markov chain in discrete time and in a finite state space
- Chapman-Kolmogorov's equation
- classification of the states
- stationary distributions
- asymptotic behaviour
Learning outcomes
The learning objectives are:
- the basic theory for Markov chains in discrete time taking values in a finite state space, in particular, the long term behavior,
- to understand via examples situations/phenomena where Markov chains can be used as mathematical models
Additional information
The course is offered approximately every second year
Description of prerequisites
Second-year courses in calculus and probability theory