MATA271 Stochastic Models (4 cr)
In this course we study mainly Markov chains. Besides investigating their properties, for example the behavior as time goes to infinity, we consider many applications, among them:
- a simple weather forecast model,
- a discrete-time share price model,
- a model to describe the risk of cancer caused by radiation
- random walk as a special case of a Markov chain
Finally we discuss that Markov Chain Monte Carlo methods work because there is a generalized Law of Large Numbers behind.
- knows Markov chains and their properties
- has studied several models where Markov chains are used
- can decide whether a certain real world situation can be modelled by Markov chains
- can analyze Markov chain models and derive properties for the real world situation
- has learned about several Markov Chain Monte Carlo methods
- has developed his/her analyzing skills and is able to decide which models are suitable for a given real world situation and which not.
The course is lectured in English and it can be completed also in Finnish.
Description of prerequisites
MATA280 Foundations of stochastics or TILA1200 Probability 1 or MATA2600 Basic course in probability.