MAU22602 Introduction to numerical analysis
Module Code | MAU22602 |
---|---|
Module Title | Introduction to numerical analysis |
Semester taught | Semester 2 |
ECTS Credits | 5 |
Module Lecturer | Prof. Stefan Sint |
Module Prerequisites | MAU11202 Advanced calculus |
Assessment Details
- This module is examined in a 2-hour examination at the end of Semester 2.
- Continuous assessment contributes 50% towards the overall mark. A Matlab onboarding assignment will be given during the first week, and assignments which mix analysis and programming will be given roughly fortnightly thereafter.
- The module is passed if the overall mark for the module is 40% or more. If the overall mark for the module is less than 40% and there is no possibility of compensation, the module will be reassessed as follows:
1) A failed exam in combination with passed continuous assessment will be reassessed by an exam in the supplemental session;
2) The combination of a failed exam and failed continuous assessment is reassessed by the supplemental exam;
3) A failed continuous assessment in combination with a passed exam will be reassessed by one or more summer assignments in advance of the supplemental session.
Contact Hours
11 weeks of teaching with 3 lectures per week.
Learning Outcomes
On successful completion of this module, students will be able to
- Describe the concepts of conditioning and sensitivity of mathematical problems, as well as the formal characterization of a mathematical problem.
- Carry out forward and backward error analysis.
- Analyze and implement common interpolation schemes and root finding methods.
- Work with vector/matrix/operator norms and relate those to the singular value decomposition of a matrix.
- Analyze and implement direct methods and stationary iterative methods for solving linear equations.
- Analyze and implement numerical integration techniques and numerical methods for solving ordinary differential equations.
Module Content
- Polynomial interpolation, root-finding, optimization and numerical integration.
- Numerical methods for solving linear systems of equations and ODEs.