Probability Theory

The course covers random variables in one and several dimensions, conditional probabilities, probability generating and characteristic functions. The multivariate normal distribution and distributions of order statistics and quadratic forms are treated. Other important probabilistic results that are covered more thoroughly compared to courses on the Bachelor level, are covergence criteria for series of random variables, the Borel Cantelli lemma, convergence through transforms, the law of large numbers, the central limit theorem and Cramér-Slutsky's theorem. Finally a deepend presentation of Poisson processes is given.