The students will learn in a practical way the main numerical techniques used in diferent areas of science. Although they will learn the mathematical background of probability and statistics, the lectures will be based on practical examples. On successful completion of this module, students will be able to:

Analyse a numberical dataset (find the mean, variance,...);

Find a simple model to describe a given dataset;

Perform a chi^2 analysis to test a model on a given dataset;

Estimate the model parameters and their standard deviations;

Module Content

FILL IN

Probability;

Random numbers;

Modelling data;

Sorting data;

Markov process;

Poisson process

Module Prerequisite

MA11S2

Assessment Detail

This module will be examined in a 2 hour examination in Trinity term.
Continuous assessment
will contribute 20% to the final grade for the module at the annual
examination session and at supplementals where applicable.