MTH2222 - Mathematics of uncertainty

Leader(s): Dr Kais Hamza

Offered

Clayton Second semester 2009 (Day)

Synopsis

Probability models. Random variables and their distributions. Multivariate distributions. Conditional distributions and conditional expectations. Generating functions. The Law of Large Numbers and the Central Limit Theorem. Introduction to stochastic processes (random walk, finite state Markov chain, branching processes). Application to statistical models. Sampling distribution. Mathematical principles of inference.

Objectives

On completion of this unit, students will understand basic concepts in statistical modelling and applied probability; apply statistical techniques to practical problems in areas of science and industry; understand the mathematical principles underlying statistical inference using the normal, binomial, t, F and chi-square distributions.

Assessment

Examination(3 hours): 70%
Continuous assessment: 30%

Contact hours

Three 1-hour lectures and one 2-hour support class per week

Prerequisites

MTH1030 or equivalent

Co-requisites

MTH2010 or MTH2021 or MTH2111

Prohibitions

MTH3222, STA2022, STA3022