Methods of simulating random variables and stochastic processes

The purpose of this thesis is fourfold: Present random number generators as well as methods of verifying them. Cover general techniques for simulating random variables. Consider methods of simulating the most common distributions, such as Normal, Exponential, Gamma, Beta, and Discrete. And finally, to discuss simula-tions of stochastic processes, including Random Walk, Poisson, Markov and Brown-ian Motion. Computer algorithms are presented with every method, MATLAB programs are given, and results are displayed in the form of graphs or histograms.