Simulation and Statistical Analysis

Full course description

Mathematical simulation is concerned with studying processes and systems. Uncertainty can be an important factor and has to be modelled properly. After modelling a complex system, various scenarios can be simulated, using Monte Carlo simulation, to gain insight. The results need to be properly interpreted and uncertainty has to be reduced. The modelling, implementation, analysis and technical aspects will be discussed as an introduction in this field. Emphasis will be on discrete event simulation and the statistical analysis of the output of simulation studies, where topics are: modelling, Poisson processes, random number generators, selecting and testing input distributions, generating random variates, statistical analysis of experiments, comparing experimental results and variance reduction. Practical exercises will be used to place the techniques in context.