Advanced Statistics: Stochastic Models
- The course is usually offered in the sommer semester.
- For passing the course and the exam, good knowledge in mathematics and statistics is required.
- Usually, the following topics are dealt with in the course: random experiment and probability, univariate and multivariate random variables, asymptotics, Poisson processes, Brownian motions, Markov processes
- In addition to the lecture exercises are offered where mathematical problems of the lecture are discussed and solved. It is suggested that students prepare the tasks beforehand
Contents and Goals
Advanced Methods in probability theory and stochasic modelling that form the basis for inference methods in economic research will be discussed. Students will learn about the computation and interpretation of probabilities and the modeling of economic circumstances through random variables and stochastic processes.
Contents and Goals are:
- Randomness and probabilities
- One-dimensional and multi-dimensional random variables
- Moments of random variables
- Parametric families of univariate and multivariate probability distributions
- Poisson processes
- Brownian motions
- Markov Chains