MTH2021 · Linear algebra with applications

Overview

Vector spaces, linear transformations. Determinants, eigenvalue problems, matrix decompositions. Inner products, least squares approximation. Applications to areas such as coding, economics, graph theory, Markov chains, differential equations

Areas of study: Applied mathematics Financial and insurance mathematics Mathematical statistics Mathematics Pure mathematics

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Apply core concepts of vector spaces and linear transformations to model and solve mathematical problems;
2. Analyse and compute eigenvalues, eigenvectors, and diagonalisation, and interpret their applications;
3. Employ inner product methods, matrix decompositions, and computational tools to address applied problems such as least-squares approximation;
4. Communicate mathematical reasoning clearly and effectively in both written and oral forms.

Workload

• Three 1-hour seminars; • One 2-hour applied class (in weeks 2-12) and • 7 hours of independent study per week.

Student experience, not official rules. Nothing here changes what the Handbook says.