6 points, SCA Band 2, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Faculty
Organisational Unit
School of Mathematical Sciences
Chief examiner(s)
Associate Professor Tim Garoni
Coordinator(s)
Associate Professor Tim Garoni
Unit guides
Synopsis
Vector spaces, linear transformations. Determinants, eigenvalue problems. Inner products, symmetric matrices, quadratic forms. LU-decomposition, least squares approximation, power method. Applications to coding, economics, networks, graph theory, geometry, dynamical systems, Markov chains, differential equations.
Outcomes
On completion of this unit students will be able to:
- Understand basic concepts related to vector spaces, including subspace, span, linear independence and basis;
- Understand basic properties of linear transformations and identify their kernel and range;
- Diagonalize real matrices by computing their eigenvalues and finding their eigenspaces;
- Understand basic concepts related to inner product spaces and apply these to problems such as least-squares data fitting;
- Apply tools from linear algebra in a wide variety of relevant situations;
- Understand and apply relevant numerical methods and demonstrate computational skills in linear algebra;
- Present clear mathematical arguments in both written and oral forms.
Assessment
End of semester examination (3 hours): 60% (Hurdle)
Continuous assessment: 40% (Hurdle)
Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for both the end-of-semester examination and continuous assessment components.
Workload requirements
Three 1-hour lectures and one 2-hour applied class per week
See also Unit timetable information