LINEAR ALGEBRA - 2017/8
Module code: MAT1034
WOLF M Dr (Maths)
Number of Credits
FHEQ Level 4
Module cap (Maximum number of students)
Overall student workload
Independent Study Hours: 101
Lecture Hours: 44
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||IN-SEMESTER TEST||25|
|Examination||EXAMINATION - 2 HOURS||75|
Prerequisites / Co-requisites
This module is an introduction to the theory and methods of Linear Algebra.
The aim of this module is to extend students' knowledge of matrices, vectors and systems of linear equations and to introduce the abstract concepts of vector spaces, linear maps and inner products.
|Students should develop an understanding of the concepts of linear algebra, and master the basic tools needed for the qualitative and quantitative description. In particular, at the end of the module the student should be able to demonstrate a proper understanding of||KCT|
|Whether systems of linear equations are soluble and be able to solve such systems by means of the Gaussian elimination;|
|The concepts of vector spaces and vector subspaces;|
|Linear (in-)dependence of vectors, basis representations of vectors, and changes of basis;|
|The concepts of linear maps, their matrix representations, eigenvalues and eigenvectors, and carry out matrix diagonalisation;|
|The concepts of inner products, norms, and orthogonality and be able to orthogonalise vectors by means of the Gram-Schmidt procedure;|
|The concept of orthogonal and unitary changes of basis;|
|The concept of self-adjoint operators;|
|Simple proofs similar to those covered in the module.|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
The module is divided into four main parts:
Systems of linear equations: rank and nullity of matrices, elementary row operations and row-echelon form, Gaussian elimination, solubility of linear equations;
Vector spaces: axiomatic development of vector spaces, linear independence of vectors, basis representations of vectors, change of basis, dimension, vector subspaces;
Linear maps: basic properties of linear maps, rank-nullity theorem, matrix representation, Cayley-Hamilton theorem, eigenvalues and eigenvectors, eigenspaces, algebraic and geometric multiplicities, diagonalisation;
Inner product spaces: inner products, norms, Cauchy-Schwarz inequality, orthogonality, orthogonal complement, Gram-Schmidt process, orthogonal and unitary changes of basis, isometries, self-adjoint operators.
Methods of Teaching / Learning
The learning and teaching strategy is designed to provide:
A detailed introduction to linear algebra and its application in other areas
Experience (through demonstration) of the methods used to interpret, understand and solve problems in linear algebra
The learning and teaching methods include:
4 x 1 hour lectures per week x 11 weeks, with lecture notes provided;
(every second week) 1 x 1 hour seminar for guided discussion of solutions to problem sheets provided to and worked on by students in advance.
The assessment strategy is designed to provide students with the opportunity to demonstrate:
That they have learnt the basic material in the field, and are able to apply it to examples and problems.
The summative assessment for this module consists of:
· In-Semester Test that constitutes 25% of the final mark;
· Final Examination that constitutes 75% of the final mark.
Formative assessment and feedback:
The students will be given exercise sheets very fortnight, and it will be suggested that they work through the examples as part of their independent study prior to attending the seminars. This will aid the students with the development of mathematical technique and knowledge. The students will receive feedback on their work during the seminars and office hours.
In addition, there will be four pieces of unassessed coursework as part of their independent study. This coursework will be marked and the students will receive detailed feedback on this work during the lectures, seminars, and office hours.
Reading list for LINEAR ALGEBRA : http://aspire.surrey.ac.uk/modules/mat1034
Programmes this module appears in
|Mathematics with Music BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics with Statistics BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics MMath||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Physics BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Mathematics and Physics MMath/MPhys||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2017/8 academic year.