Aims and Fit of Module

The module aims to provide a rigorous introduction to probability and mathematical statistics particularly for math majored students. It also enables students to discuss the potential scope of the applications and illustrate typical ways of analysis, and provide an appropriate technical background for related higher level MTH modules.

Learning outcomes

A.	describe statistical data;

B. apply basic probability theory to solve related problems;

C. provide good knowledge on typical distributions such as Bernoulli, Binomial, Geometric, Uniform, Poisson, Exponential and Normal distributions and their applications;

Method of teaching and learning

The teaching philosophy of the module follows very much the philosophy of Syntegrative Education. This has meant that the teaching delivery pattern, which follows more intensive block teaching, allows more meaningful contribution from industry partners. This philosophy is carried through also in terms of assessment, with reduction on the use of exams and increase in coursework, especially problem-based assessments that are project focused. The delivery pattern provides space in the semester for students to concentrate on completing the assessments.
This module will be delivered by a combination of formal lectures, seminars and tutorials.