Learning outcomes

The goal is to get familiar with the basics of probability theory and with some discrete time stochastic processes.

Contents

Markov chains, stationarity and ergodicity. The concepts are introduced using examples from meteorology, biology, medicine and finance.

Teaching methods

Teaching method	Contact	Online
Lectures	0 h	28 h
Exercises	14 h	0 h

Evaluation

Numeric 1-5.

Study materials

1. Guttorp, P., Stochastic modeling of scientific data. Chapman & Hall, 1995.
2. Häggström, O., Finite Markov chains and algorithmic applications.
3. Tan, W.-Y., Stochastic models with applications to genetics, cancers, AIDS and other biomedical systems.

Belongs to following study modules