Introduce the main theories and methods in Computational Mathematics
Illustrate the application of computational techniques in Numerical Analysis
Module learning outcomes
On completion of the module, student will:
Have a working knowledge of basic mathematical techniques in series, differentiation and linear algebra
Understand how to use bisection, fixed point iteration and Newton's method to solve non-linear equations
Know how to solve linear equations both with and without constraints
Be able to apply Least-Squares to fit a function to data
Understand how to optimise multivariate functions
Assessment
Task
Length
% of module mark
University - closed examination Numerical Analysis (NUMA)
1.5 hours
100
Special assessment rules
None
Reassessment
Task
Length
% of module mark
University - closed examination Numerical Analysis (NUMA)
1.5 hours
100
Module feedback
9 hours of problem classes 5 hours of lab-based practical classes.
Indicative reading
**** K. A. Stroud, Engineering Mathematics, Palgrave Macmillan, 2001
+++ Chapra and Canale, Numerical Methods for Engineers, McGraw-Hill Higher Education, 2002
Coronavirus (COVID-19): changes to courses
The 2020/21 academic year will start in September. We aim to deliver as much face-to-face teaching as we can, supported by high quality online alternatives where we must.
Find details of the measures we're planning to protect our community.