# 2015/16 Undergraduate Module Catalogue

## MATH2601 Numerical Analysis with Computation

### 15 creditsClass Size: 40

**Module manager:** Dr J Niesen**Email:** J.Niesen@leeds.ac.uk

**Taught:** Semester 1 View Timetable

**Year running** 2015/16

### Pre-requisite qualifications

MATH1920 and [MATH1010 or (MATH1050 and MATH1060) or (MATH1050 and MATH1331)], or equivalent.### This module is mutually exclusive with

MATH2600 | Numerical Analysis |

**This module is not approved as a discovery module**

### Objectives

Most of the problems that students meet when they are introduced to, for example, integration or differential equations, will have nice analytic solutions. In real life though this is typically not the case and so solutions have to be evaluated numerically (ie with the aid of a computer). This module explains how to express mathematical operations in terms of operations that can be performed on a computer. It is a good preparation for the Level 3 module in Numerical Methods (MATH 3473). This module also involves a practical implementation of the algorithmic ideas. Students should improve their programming skills begun in MATH1920, and gain confidence and facility with computational mathematics.In order to pass the module, students must pass the MATH2600 component (which is at least 40% on exam and in-course assessment combined) and score at least 40% on the Computer Exercises.

**Learning outcomes**

On completion of this module, students should be able to:

- describe how errors arise in computations;

- solve simple non-linear equations by root-finding techniques;

- calculate the interpolating polynomial through discrete data points;

- derive and use quadrature formulae based on integration of polynomial interpolates;

- write down suitable numerical schemes for solving first order ordinary differential equations;

- solve linear systems of algebraic equations using Gaussian elimination and LU factorisation;

- implement numerical algorithms computationally and interpret the results of programs;

- understand some of the practical issues associated with mathematical programming.

### Syllabus

- Introduction. Computer arithmetic. Errors; round-off error, truncation error.

- Solution of nonlinear equations in one variable. Bisection method; fixed point iteration; Newton-Raphson iteration; secant method. Order of convergence.

- Interpolation. Lagrange interpolation; error term. cubic splines.

- Numerical integration. Trapezoidal rule. Method of undetermined coefficients. Simpson's rule. Newton-Cotes formulae. Composite integration methods. Richardson extrapolation; Romberg integration.

- Ordinary differential equations (initial value problems). Euler's method; errors. Runge-Kutta methods. Multi-step methods. Stability.

- Linear systems of algebraic equations. Gaussian elimination. Pivoting. LU factorisation.

- Practical implementation of theoretical principles in Python.

- Investigation of computational aspects of numerical analysis.

### Teaching methods

Delivery type | Number | Length hours | Student hours |

Workshop | 10 | 1.00 | 10.00 |

Lecture | 22 | 1.00 | 22.00 |

Practical | 5 | 2.00 | 10.00 |

Tutorial | 5 | 1.00 | 5.00 |

Private study hours | 103.00 | ||

Total Contact hours | 47.00 | ||

Total hours (100hr per 10 credits) | 150.00 |

### Private study

Students should spend 68 hours in the same way as for MATH2600. The remaing 35 hours are spent writing computer code, analysing results, and writing up work.### Opportunities for Formative Feedback

Five fortnightly pieces of coursework are marked and feedback given. Of these, 2 are assessed towards the final module grade.### Methods of assessment

**Coursework**

Assessment type | Notes | % of formal assessment |

Computer Exercise | In order to pass the module, students must pass the exam and score at least 40% on the Computer Exercises. | 30.00 |

In-course Assessment | * | 10.00 |

Total percentage (Assessment Coursework) | 40.00 |

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

**Exams**

Exam type | Exam duration | % of formal assessment |

Standard exam (closed essays, MCQs etc) | 2 hr 00 mins | 60.00 |

Total percentage (Assessment Exams) | 60.00 |

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

### Reading list

The reading list is available from the Library websiteLast updated: 07/05/2015

## Browse Other Catalogues

- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue

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