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


To study on a distance education will give you different opportunities than on-campus teaching. It means that, to a large extent, you will be able to plan your studies yourself, both in terms of time and place.

However, keep in mind that most distance education includes a number of compulsory digital lectures and digital seminars during the weekdays. Some distance education also include compulsory get-togethers, for which you will have to travel to Växjö or Kalmar.

There are a number of different ways to be a distance student, the common denominator being that a large part of your study work is carried out on the web. You communicate with the teacher and your fellow students using a learning platform with discussion forums, group work, recorded lectures or video meetings using a web cam.

Students working