Monte Carlo methods
7.5 credits
The course contains:
•General generation of one-dimensional random numbers, discrete and continuous: the inverse method, the acceptance-rejection technique, the compositon approach
•Generating specific one-dimensional random numbers: normal random numbers by the polar method, Poisson random variables, binomial random variables
•Generation of Poisson processes: homogenous and nonhomogenous, one-dimensional and two-dimensional
•Generation of multidimensional normal random numbers
•Generation of variables from copula models
•Variancereductiontechniques:useantitheticvariablesandcontrolvari- ates, conditioning, stratigic sampling, non-normalized and normalized importance sampling, latin hypercube sampling
•Statistical analysis of simulated data: the sample mean and sample variance, interval estimates of a population mean, bootstrapping technique for estimating mean square errors
•Statistical validation techniques: goodness of fit tests
Distance – study where you are
Distance learning can be structured in different ways – it may be entirely online, or include a few on-campus sessions or meetings at one of our learning centres. The common factor is that most of the learning happens online.
You communicate with your teacher and fellow students through a learning platform, which provides access to discussion forums, group work opportunities, and digital meetings. In many cases, you also have access to recorded lectures via the platform.
The advantage of distance learning is its flexibility – ideal for those who want more freedom to decide when and where to study. However, keep in mind that some mandatory elements of your programme may take place during working hours, even if they are conducted online.
Build your own degree
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