MATH 642 - Probabilistic Simulation

3 Credit(s)

Description:
Simulation is a powerful tool in dealing with systems that are too complex to solve analytically. Probabilistic simulations using Monte Carlo techniques provide a way to emulate the behavior of the system and generate random samples for each output variable of interest that can then be analyzed by statistical methods. This course provides a practical introduction to Monte Carlo simulations and statistical methods for analyzing random samples generated by such simulations. The following topics will be discussed: random number generators, generating continuous and discrete random variables, generating multivariate random variables, statistical analysis of the output data and methods for fitting probability distributions to the data. The course will emphasize the practical implementations of these techniques using the R statistical program language.

039231:1

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