Foundations of probability theory
- Definitions of probability, conditional probability
- Random variables, dependencies, independence assumptions, 
- Marginal and joint probabilities
- Distributions and density functions
- Characteristics: expected values, variance, standard deviation, moments
Practical representations for joint probabilities
- Bayessche Netzwerke
- Semantik, Entscheidungsprobleme, exakte und approximative Algorithmen
Stochastic processes
- Stationarity, ergodicity
- Correlations
- Dynamic Bayesian networks, Hidden Markov networks, Kalman filters, queues
Detection & estimation
- Detectors
- Estimation rules and procedures
- Hypothesis and distribution tests
- Stochastic regression

- Methoden der statistischen Inferenz, Likelihood und Bayes, Held, L., Spektrum 2008
- Stochastik für Informatiker, Dümbgen, L., Springer 2003
- Statistik: Der Weg zur Datenanalyse, Fahrmeir, L., Künstler R., Pigeot, I, Tutz, G., Springer 2010
- Stochastik, Georgii, H.-O., deGruyter, 2009
- Probability and Random Processes, Grimmett, G., Stirzaker, D., Oxford University Press, 2001
- Programmieren mit R, Ligges, U., Springer 2008