Gwybodaeth Modiwlau

Module Identifier
MA21410
Module Title
Linear Algebra
Academic Year
2022/2023
Co-ordinator
Semester
Semester 2
Other Staff

Course Delivery

 

Assessment

Assessment Type Assessment length / details Proportion
Semester Exam 2 Hours   (Written Examination)  100%
Supplementary Exam 2 Hours   (Written Examination)  100%

Learning Outcomes

On completion of this module, a student should be able to:
1. determine whether given algebraic structures are vector spaces;
2. apply criteria for subspaces of a vector space;
3. determine bases for vector spaces;
4. prove and apply propositions in the theory of vector spaces;
5. describe the concept of linear transformation;
6. calculate matrices representing linear transformations;
7. determine the rank and nullity of linear transformations and matrices;
8. perform calculations in inner product spaces;
9. diagonalise matrices, especially symmetric matrices.

Brief description

In this module the concept of a vector space is introduced. This develops some ideas which have occurred in the first year course. It will be seen that superficially different problems in mathematics can be unified. For example, the solution of systems of linear equations and linear diffential equations are essentially the same process and can be dealt with simultaneously in this context.

Aims

To develop some matrix theory techniques which have occurred in the first year courses in an abstract setting. To introduce the concepts of a vector space and a mapping between vector spaces. To develop further techniques for computation in vector spaces and to show that this is the correct framework to consider linear problems in a unified way.

Content

1. VECTOR SPACES: Definition and examples, subspaces, spanning sets, linear independence, basis and dimensions.
2. LINEAR TRANSFORMATIONS: Definition and examples, the matrix of a linear transformation, change of basis. The kernel and image of a linear transformation, rank and nullity. The dimension theorem.
3. INNER PRODUCT SPACES: Definition and examples. Orthogonality and Gram-Schmidt orthogonalisation process.
4. DIAGONALISATION OF MATRICES: Eigenvalues and eigenvectors, characteristic equation. Diagonalisation of matrices.

Module Skills

Skills Type Skills details
Adaptability and resilience Students are expected to develop their own approach to time-management and to use the feedback from marked work to support their learning.
Co-ordinating with others Students will be encouraged to work in groups to solve problems.
Creative Problem Solving The assignments will give the students opportunities to show creativity in finding solutions and develop their problem solving skills.
Digital capability Use of the internet, Blackboard, and mathematical packages will be encouraged to enhance their understanding of the module content and examples of application
Professional communication Students will be expected to submit clearly written solutions to set exercises.
Subject Specific Skills Broadens exposure of students to topics in mathematics, and an area of application that they have not previously encountered.

Notes

This module is at CQFW Level 5