Programme And Module Handbook
 
Course Details in


If you find any data displayed on this website that should be amended, please contact the Curriculum Management Team.

Module Title LI Numerical Methods & Programming
SchoolMathematics
Department Mathematics
Module Code 06 25669
Module Lead Dr Chris Good
Level Intermediate Level
Credits 10
Semester Full Term
Pre-requisites LC Vectors, Geometry & Linear Algebra - (06 25664) LC Real Analysis & the Calculus (BNatSci) - (06 25764) LC Real Analysis & the Calculus - (06 25660)
Co-requisites
Restrictions None
Contact Hours Lecture-0 hours
Seminar-0 hours
Tutorial-0 hours
Project supervision-0 hours
Demonstration-0 hours
Practical Classes and workshops-0 hours
Supervised time in studio/workshop-0 hours
Fieldwork-0 hours
External Visits-0 hours
Work based learning-0 hours
Guided independent study-0 hours
Placement-0 hours
Year Abroad-0 hours
Exclusions
Description Many problems arising in mathematics cannot be solved exactly. In such cases, one approach is to use numerical methods implemented on a computer to find approximate but nevertheless usefully accurate solutions. This module introduces the basic techniques of such numerical methods, involving one or more computer packages, and uses these to illustrate and explore mathematics graphically and numerically, perform numerical routines, and run simulations involving random numbers. At the same time, it the basic ideas of computer programming are introduced such as writing simple programmes, the process of debugging code and the sources and effects of errors in the use of floating point numbers.
Learning Outcomes By the end of the module students should be able to:
  • describe and analyze different types of errors and discuss coherently the errors in numerical calculations performed;
  • apply and discuss various numerical methods to find zeroes of functions, approximate functions using interpolation techniques, different ways to calculate integrals, to solving initial value problems for ordinary differential equations
  • discuss simple simulations and generate random numbers
  • demonstrate knowledge and understanding of design, testing and debugging strategies in the context of scientific programming
  • demonstrate knowledge and understanding of essential syntax elements of the relevant programming language and of basic programming structures
  • use such knowledge and understanding to design, implement and evaluate computer code for well specified problems
  • deploy appropriate mechanisms for improving data entry and data output
  • demonstrate knowledge and understanding of number representations and the various sources of errors affecting computational results
  • use such knowledge and understanding in the analysis and evaluation of numerical results
Assessment 25669-01 : Raw Module Mark : Practical (0%)
25669-02 : Final Module Mark : Coursework (100%)
Assessment Methods & Exceptions 100% on work done during semester
Other
Reading List