NUMBER SYSTEMS AND LINEAR ALGEBRA

MAT4NLA

2018

Credit points: 15

Subject outline

In this subject, students learn and apply mathematical concepts and develop skills that provide a foundation for all studies in mathematical sciences, including data science. Students review and extend their knowledge of algebra, functions, sets and number systems with significant coverage of complex numbers adding to their repertoire. After consideration of sequences and series, students proceed to a module on Logic and Proof. Students also explore a coherent treatment of vectors and vector geometry that includes matrices and solutions of systems of linear equations via the Gauss-Jordan algorithm, and brief treatment of eigenvalues and eigenvectors. An emphasis is placed on students improving their understanding of mathematical concepts and results so they can be appropriately applied, and development of their reasoning skills and ability to clearly present written arguments, essential in both study and employment. 



SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorKatherine Seaton

Available to Study Abroad StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites Students must be enrolled in SMDS and require coordinators approval.

Co-requisitesN/A

Incompatible subjects MAT1CNS, MAT1CPE, MAT1CLA, MAT1CA, MAT1CB, MAT1NLA

Equivalent subjectsN/A

Special conditions May not be taken by students who are currently enrolled in MAT1ICA.

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsSurvival Skills for Tertiary MathsPrescribed2017Department of Mathematics and Statistics, La Trobe University
ReadingsNotes on Number SystemsPrescribed2017Department of Mathematics and Statistics, La Trobe University
ReadingsNotes on Linear AlgebraPrescribed2017Department of Mathematics and Statistics, La Trobe University
ReadingsNotes on Logic and ProofPrescribed2017Department of Mathematics and Statistics, La Trobe University

Graduate capabilities & intended learning outcomes

01. Manipulate and find solution sets to equalities and inequalities involving algebraic expressions.

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Reinforcement practice, feedback and assessment are provided through assignments and online activities.

02. Calculate limits of sequences and sums of infinite series.

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Reinforcement practice, feedback and assessment are provided through assignments and online activities.

03. Solve algebraic problems involving complex numbers, including the use of geometric interpretations to find and describe solutions.

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Reinforcement practice, feedback and assessment are provided through assignments and online activities.

04. Apply vector techniques and matrix operations to find and describe objects in three dimensional space, and find eigenvalues and eigenvectors in two dimensions.

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Reinforcement practice, feedback and assessment are provided through assignments and online activities.

05. Use Gaussian elimination to solve systems of linear equations and interpret the solutions geometrically.

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Reinforcement practice, feedback and assessment are provided through assignments and online activities.

06. Discuss the application of the techniques of mathematics to data science

Activities:
Students are introduced to fundamental concepts in lectures and practice using ideas and techniques covered, under staff supervision, in Practice Classes. Assessment task (essay) provides opportunity to research and discuss applications

07. Present mathematical thinking in written form in a meaningful and succinct way using both words and mathematical notation.

Activities:
Emphasis is placed on this in lectures and practice classes and assignments have specifically allocated marks for, and feedback on improvements to, written mathematical communication.

Subject options

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Start date between: and    Key dates

Melbourne, 2018, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorKatherine Seaton

Class requirements

Lecture Week: 10 - 22
Two 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"Timetable with MAT1NLA"

Practical Week: 10 - 22
Two 1.0 hours practical per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
3 hour exam (equiv 3000 words)65 01, 02, 03, 04, 05, 06, 07
5 assignments (typically 3-4 pages each, equiv 400 words each)20 01, 02, 03, 04, 05, 06, 07
Essay (1500 words)15 06, 07