• Part I: Probability spaces, random variables, probability distributions and probability densities, conditional probability, Bayes' formula, mathematical expectation, moments. Part II: Sampling distributions, decision theory, estimation (theory and applications), hypothesis testing (theory and applications), regression and correlation, analysis of variance, non-parametric tests.

    For further information see the academic catalog: IAM530

  • \( \LaTeX \) and Matlab; Basic Commands and Syntax of \( \LaTeX \) and Matlab; Working within a Research Group via Subversion; Arrays and Matrices; Scripts and Function in Matlab; Commands and Environments in \( \LaTeX \); More on Matlab Functions; Toolboxes of Matlab; Packages in \( \LaTeX \); Graphics in Matlab; Handling Graphics and Plotting in \( \LaTeX \); Advanced Techniques in Matlab: memory allocation, vectoristaion, object orientation, scoping, structures, strings, file streams.

    For further information see the academic catalog: IAM591

  • Generating Random Numbers; Basic Principles of Monte Carlo; Numerical Schemes for Stochastic Differential Equations; Simulating Financial Models; Jump-Diffusion and Levy Type Models; Simulating Actuarial Models; Markov Chain Monte Carlo Methods.

    For further information see the academic catalog: IAM757