- Describe and apply basic concepts of probability theory such as outcome, event, probability, conditional probability, independence, stochastic variable, distribution, distribution function, frequency function, density, expectation, moment, (co)variance, correlation coefficient and moment generating function.
- Adequately model chance events.
- Describe and use the most important discrete and continuous distributions and their properties.
- Describe and apply moment generating functions, the Markov and Chebyshev inequalities, the weak and strong laws of large numbers and the central limit theorem.
- Use the technique of conditioning for the computation of probabilities and expectations.