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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Linear Mathematics II
Module Code MS104
School School of Mathematical Sciences
Module Co-ordinatorSemester 1: Thomas Brady
Semester 2: Thomas Brady
Autumn: Thomas Brady
Module TeachersThomas Brady
NFQ level 6 Credit Rating 5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
None
Examination in August repeat exam diet
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
Lecture24Lectures
Tutorial11Tutorial and examples class
Independent Study44Solving exercises on tutorial sheets
Independent Study22Preparation for class tests and final exam
Independent Study24Assimilating 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

Vector Spaces
Spaces of real and complex vectors; linear mappings; subspaces; linear independence; basis and dimension; row space, column space and null space; rank and nullity

Inner product spaces
standard inner products; Cauchy-Schwarz inequality; angle and orthogonality; orthonormal bases and Gram-Schmidt procedure; orthogonal matrices; positive and negative definite matrices; least squares approximation; least square solutions; orthogonal projections

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

Assessment Breakdown
Continuous Assessment20% Examination Weight80%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentHomework assignments and/or in-class tests20%As required
Reassessment Requirement Type
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

  • H. Anton and C. Rorres: 2005, Elementary Linear Algebra - Applications Version, 9th or 10th, John Wiley & Sons, Inc.,
Other Resources

None
Programme or List of Programmes
ACMBSc in Actuarial Mathematics
BPMBSc in Psychology with Mathematics
BSSAStudy Abroad (DCU Business School)
BSSAOStudy Abroad (DCU Business School)
CAFMCommon Entry, Actuarial, Financial Maths
DSBSc in Data Science
HMSAStudy Abroad (Humanities & Soc Science)
HMSAOStudy Abroad (Humanities & Soc Science)
IESAStudy Abroad (Institute of Education)
IESAOStudy Abroad (Institute of Education)
SHSAStudy Abroad (Science & Health)
SHSAOStudy Abroad (Science & Health)
SMPSCSingle Module Prog Science and Health
Date of Last Revision18-JUN-08
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