## COMP2421 Numerical Computation

### 10 creditsClass Size: 300

Module manager: Professor Netta Cohen
Email: n.cohen@leeds.ac.uk

Taught: Semester 1 View Timetable

Year running 2020/21

### Pre-requisites

 COMP1421 Fundamental Mathematical Concepts COMP1721 Object Oriented Programming

This module is not approved as a discovery module

### Module summary

Accuracy of floating-point computation. Standard numerical algorithms for linear equation systems, nonlinear equations, ordinary differential equations and data interpolation. The design of robust and efficient implementations in code.

### Objectives

On completion of this module, students should be able to:
- Appreciate the role of numerical computation in computer science;
- Choose a computational algorithm appropriately, accounting for issues of accuracy, reliabilty and efficiency;
- Understand how to assess/measure the error in a numerical algorithm and be familar with how such errors are controlled;
- Implement simple numerical algorithms

Learning outcomes
On completion of the year/programme students should have provided evidence of being able to:
-demonstrate a broad understanding of the concepts, information, practical competencies and techniques which are standard features in a range of aspects of the discipline;
-apply generic and subject specific intellectual qualities to standard situations outside the context in which they were originally studied;
-appreciate and employ the main methods of enquiry in the subject and critically evaluate the appropriateness of different methods of enquiry;
-use a range of techniques to initiate and undertake the analysis of data and information;
-effectively communicate information, arguments and analysis in a variety of forms;

### Syllabus

Approximation: converting a real-world problem, via a mathematical model, to a form which can be understood by a computer; discretising a continuous model; measuring, analysing and controlling approximation errors; balancing accuracy and efficiency. Static systems: simple iterative methods for solving nonlinear scalar equations; direct and iterative methods for solving linear systems of equations.
Evolving systems: differentiation as rate of change and as the limit of a gradient (including derivatives of simple functions); initial value ordinary differential equations, simple methods for initial value problems.

### Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

 Delivery type Number Length hours Student hours Example Class 10 1.00 10.00 Lecture 20 1.00 20.00 Private study hours 70.00 Total Contact hours 30.00 Total hours (100hr per 10 credits) 100.00

### Opportunities for Formative Feedback

Coursework and tutorial / lab sessions.

### Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Coursework
 Assessment type Notes % of formal assessment Assignment Assignment 1 10.00 Assignment Assignment 2 10.00 Total percentage (Assessment Coursework) 20.00

This module is re-assessed by exam only

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 2 hr 00 mins 80.00 Total percentage (Assessment Exams) 80.00

This module is re-assessed by exam only