620-131 Scientific Programming & Simulation

Passing 620-131 precludes subsequent credit for 620-152 or 620-160.

One of 620-120 (MUPHAS Mathematics), 620-121, 620-140, 620-141, 620-211.

Many real world phenomena - financial markets, insurance risk, gambling, telecommunications networks - are best modelled as random processes involving uncertainty. They can be studied by performing a computer simulation of the process and treating the results as the outcome of an experiment.

In this subject, students develop high order problem-solving skills for tackling problems with an uncertain or random component. They learn how to select probability models to describe real world processes. They learn the basics of a general-purpose programming language, so they can implement computer simulations. They learn simple statistical inference, so they can interpret the results of their simulations.

Students completing the subject develop the ability to read, write, debug and adapt simple computer programs, using techniques including conditional branching, loops, arrays and subroutines. They learn about convergence of sequences and series, and applications of convergence to solving equations. They learn to carry out probability calculations using standard distributions arising from Bernoulli trials and the Poisson process and to write programs to simulate these processes. They compare traditional and Monte Carlo methods of numerical integration. They learn about distributions of sample statistics, leading to confidence intervals, hypothesis testing and regression modelling.

Assessed computer laboratory tasks and project work during semester (30%) and a 3-hour end-of-semester written examination (70%).