Numerical Methods

The details
Mathematical Sciences
Colchester Campus
Undergraduate: Level 5
Monday 13 January 2020
Friday 20 March 2020
01 October 2019


Requisites for this module



Key module for

BSC G100 Mathematics,
BSC G102 Mathematics (Including Year Abroad),
BSC G103 Mathematics (Including Placement Year),
BSC G104 Mathematics (Including Foundation Year),
BSC 5B43 Statistics (Including Year Abroad),
BSC 9K12 Statistics,
BSC 9K13 Statistics (Including Placement Year),
BSC 9K18 Statistics (Including Foundation Year),
BSC G1G4 Mathematics with Computing (Including Year Abroad),
BSC G1G8 Mathematics with Computing (Including Foundation Year),
BSC G1GK Mathematics with Computing,
BSC G1IK Mathematics with Computing (Including Placement Year)

Module description

The module introduces the students to practical techniques for carrying out numerical computations on a range of mathematical problems. Students will be expected to have an elementary acquaintance with Matlab (MA182-4-SP-CO. An introduction to Matlab will also be provided via Moodle and for those who need it).

Module aims


1. An introduction to practical computations
- Algorithms
- Simple examples
- Pitfalls

2. Solving single nonlinear equations
- Bisection method
- Regula-Falsi method
- Newton-Raphson method

3. Numerical linear algebra
- Gaussian elimination
- Partial pivoting
- Iterative methods

4. Numerical solution of ordinary differential equations
- Euler method
- Runge-Kutta methods
- Linear multi-step methods

5. Simple approximation
- Polynomial interpolation
- Optimal interpolation points
- Fourier and trigonometric series

Module learning outcomes

On completion of the module, students should be able to:
- appreciate the processes and pitfalls of mathematical approximation
- demonstrate knowledge and understanding of mathematical computing
- motivate and describe the derivation of the numerical algorithms covered in the module
- carry out simple numerical processes "by hand"
- implement and run algorithms developed in Matlab
- evaluate, contrast and reflect upon the numerical results arising from different algorithms

Module information

No additional information available.

Learning and teaching methods

The module runs at 3 hours per week in the autumn term. There are two lectures and one class/laboratory each week. In the summer term, 3 revision lectures are given.


This module does not appear to have any essential texts. To see non-essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework Homework 1 10/02/2020 50%
Coursework Homework 2 16/03/2020 50%
Exam 120 minutes during Summer (Main Period) (Main)

Overall assessment

Coursework Exam
20% 80%


Coursework Exam
0% 100%
Module supervisor and teaching staff
Dr Xinan Yang, email, Dr Joe Bailey (
Dr Xinan Yang (



External examiner

No external examiner information available for this module.
Available via Moodle
Of 38 hours, 28 (73.7%) hours available to students:
10 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).


Further information
Mathematical Sciences

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