Registry

Module Specifications

Current Academic Year 2012 - 2013
Please note that this information is subject to change.

Module Title	Linear Mathematics II
Module Code	MS104
School	School of Mathematics
Online Module Resources
Module Co-ordinator	Semester 1: David Reynolds Semester 2: David Reynolds Autumn: David Reynolds
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

The purpose of this module is to introduce to students who have successfully completed Linear Mathematics 1 further foundational topics in Linear Algebra. The emphasis is on students gaining a sound knowledge of basics and fundamental computational skills. Eigenvalues and eigenvectors are important in calculus of several variables, probability and statistics.The course is delivered through a combination of lectures, and tutorials facilitated by a tutor.

Learning Outcomes

1. Demonstrate computational skills by solving wide range of drill problems related to the indicative syllabus
2. State selected definitions and theorems related to the indicative syllabus
3. Solve exercises that test understanding of these definitions and theorems
4. Explain arguments used to prove selected theorems in special cases

Workload	Full-time hours per semester
*Type*	*Hours*	*Description*
Lecture	24	Lectures
Tutorial	11	Tutorial and examples class
Independent learning	44	Solving exercises on tutorial sheets
Independent learning	22	Preparation for class tests and final exam
Independent learning	24	Assimilating lecture material
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Determinants.
Determinants by cofactor expansion; evaluating determinants using row and column operations; properties of determinants; adjugate; finding inverses.

Inner product spaces.
standard inner products; Cauchy-Schwarz inequality; angle and orthogonality; orthonormal bases andGram-Schmidt procedure; orthogonal matrices; positive and negative definite matrices; least squaresapproximation.

Eigenvalues and Eigenvectors.
Eigenvalues and eigenvectors; diagonalisation; Diagonalisation of symmetric and Hermitian matrices.

Assessment Breakdown
Continuous Assessment	20%	Examination Weight	80%

Course Work Breakdown
Type	Description	% of total	Assessment Date
In Class Test	Class Test on determinants	10%	Week 21
In Class Test	Class test on eigenvalues and eigenvectors	10%	Week 25

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 3

Indicative Reading List