Registry

Module Specifications

Current Academic Year 2009 - 2010
This information is provisional and subject to change.

Module Title	Probability
Module Code	CA219
School	Computing
Online Module Resources
Module Co-ordinator	Prof Jane Horgan	Office Number	L2.45
Level	2	Credit Rating	5
Pre-requisite	None
Co-requisite	None

Module Aims

To introduce the basic probability concepts and their applications to computer disciples;

To provide an understanding of discrete and continuous distributions;

To cover the essentials of the statistical computing system R.

Learning Outcomes

At then end of the module the student will:

 have a thorough understanding of basic probability;

recognise problems that may be solved using the standard discrete and continous statistical models;

know how to obtain expectations of discrete and continuous random variables;

have developed a package in R to generate pdfs and cdfs of discrete distributions

Indicative Time Allowances
	Hours
Lectures	24
Tutorials	12
Laboratories	12
Seminars	0
Independent Learning Time	27

Total	75
Placements
Assignments

NOTE

Assume that a 5 credit module load represents approximately 75 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module.

Indicative Syllabus

Summarising and displaying statistical data in R;

Introduction to probability: discrete sample spaces; axioms; addition and multiplication laws; conditional probability and independence; reliability of systems; Bayes theorem; ·

Discrete Random Variables: Bernouilli, hypergeometric, binomial, geometric and Poisson distributions; expectation;

Sampling Inspection Schemes: Single and double sampling; operating characteristic function; average outgoing quality; consumers''''''''s and producer''''''''s risks.

Continuous Random Variables: Uniform, exponential and normal

distributions; normal approximation to binomial.

Tchebechev''''''''s and Markov''''''''s inequalities ·