LINEAR ALGEBRA

MAT2LAL

2020

Credit points: 15

Subject outline

Linear algebra is one of the cornerstones of modern mathematics. Simple geometrical ideas, such as lines, planes, rules for vector addition and dot products arise in many places, including calculus, signal processing, mechanics, differential equations and numerical analysis. This subject is an introduction to the mathematics which allows these geometrical ideas to be applied in non-geometrical contexts. Using the key ideas of linear independence and spanning sets we develop the notion of a basis for a vector space. The fact that the space of functions is a vector space lies at the heart of Fourier approximation.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Peter Van Der Kamp

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 2 - UG

Exchange Students: No

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: MAT1CLA OR (MAT1CDE AND MAT1NLA)

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Learning resources

Printed subject text available from University Bookshop

Resource Type: Book

Resource Requirement: Prescribed

Author: N/A

Year: N/A

Edition/Volume: N/A

Publisher: N/A

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

DISCIPLINE KNOWLEDGE AND SKILLS

Intended Learning Outcomes

01. Perform calculations using vectors and matrices, including application of the Gaussian algorithm.

02. Describe vector spaces, vector subspaces, and the linear maps between them in terms of bases.

03. Apply the methods of linear algebra in applications including: Fourier approximations, differential equations, quadratic forms, and approximation.

04. Communicate understanding of basic definitions and utilise them to prove elementary results in linear algebra.

05. Communicate understanding of linear algebra using both words and precise mathematical symbolism.

Bendigo, 2020, Semester 2, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Enrolment information: N/A

Subject Instance Co-ordinator: Christopher Lenard

Class requirements

LectureWeek: 31 - 43
Two 1.00 hour lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

PracticalWeek: 31 - 43
Two 1.00 hour practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment element	Comments	Category	Contribution	Hurdle	%	ILO*
5 fortnightly assignments (total 1500 word equiv)	N/A	N/A	N/A	No	30	SILO1, SILO2, SILO3, SILO4, SILO5
One 3-hour examination	N/A	N/A	N/A	No	70	SILO1, SILO2, SILO3, SILO4, SILO5

Melbourne (Bundoora), 2020, Semester 2, Day