This paper is an introduction to the fundamental ideas and techniques of linear algebra and the application of these ideas to computer science and the sciences.

The principal aim of this paper is for students to develop a working knowledge of the central ideas of linear algebra: vector spaces, linear transformations, orthogonality, eigenvalues and eigenvectors, and the spectral theorem.

We will explore applications of these ideas in science, computer science and engineering.

Paper title | Linear Algebra |
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Paper code | MATH202 |

Subject | Mathematics |

EFTS | 0.15 |

Points | 18 points |

Teaching period | Semester 1 (On campus) |

Domestic Tuition Fees (NZD) | $955.05 |

International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |

- Prerequisite
- MATH 140 or MATH 170
- Restriction
- MATH 242, MATH 341
- Schedule C
- Arts and Music, Science
- Eligibility
MATH 202 is compulsory for the Mathematics major. It is particularly important for students majoring in Statistics, Computer Science and Physics, and is relevant and useful for any student in the sciences who forsees themselves working with and analysing data.

- Contact
- Teaching staff
Dr Dominic Searles

- Paper Structure
Main topics:

- Vector spaces over the real and complex numbers (mainly finite-dimensional), vector subspaces
- Linear combinations, linear independence and span, bases, dimension, extending bases of subspaces, sum of subspaces, direct sums
- Linear transformations and their properties, kernel and range, rank-nullity theorem
- Representation of linear transformations by matrices, coordinate vectors, composition of linear transformations corresponds to products of matrices
- Diagonalisation, invariant subspaces, eigenvalues and eigenvectors
- Inner products, orthogonality, orthogonal projections, Cauchy-Schwartz inequality, inner-product norm, orthonormal bases, Gram-Schmidt process, orthogonal complements, minimisation problems
- The adjoint of a linear transformation, self-adjoint and normal transformations, the real and complex spectral theorems, the singular-value decomposition of a matrix

- Textbooks
Sheldon Axler, Linear Algebra Done Right, 3rd ed, Springer (free to download e-book through UoO library).

- Graduate Attributes Emphasised
- Critical thinking.

View more information about Otago's graduate attributes. - Learning Outcomes
Students who successfully complete this paper will develop a working knowledge of the central ideas of linear algebra and the applications of these ideas in science, computer science and engineering.

- Vector spaces
- Linear transformations
- Orthogonality
- Eigenvalues and eigenvectors
- The spectral theorem