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2019/20 Taught Postgraduate Module Catalogue

MATH5835M Statistical Computing

15 creditsClass Size: 60

Module manager: Dr Jochen Voss
Email: J.Voss@leeds.ac.uk

Taught: Semester 1 View Timetable

Year running 2019/20

Pre-requisites

MATH2715Statistical Methods

This module is not approved as an Elective

Module summary

The use of computers in mathematics and statistics has opened up a wide range of tech- niques for studying otherwise intractable problems and for analysing very large data sets."Statistical computing" is the branch of mathematics which concerns these techniques for situations which either directly involve randomness, or where randomness is used as part of a mathematical model. This module gives an overview of the foundations and basic methods in statistical computing.One of the most important ideas in statistical computing is, that often properties of a stochastic model can be found experimentally, by using a computer to generate many random instances of the model, and then statistically analysing the resulting sample. The resulting methods are called Monte Carlo methods, and discussion of such methods forms the main focus of this module.

Objectives

On completion of this module, students should:

(a) be able to apply standard methods for random number generation
(b) understand principles and methods of stochastic simulation;
(c) be able to apply different Monte Carlo methods;
(d) be familiar with software for advanced statistical computing;
(e) be able to implement statistical algorithms for a given problem.

Skills outcomes
Transferable Skills: computing and programming skills; report writing.


Syllabus

(a) Random number generation
(b) Monte-Carlo methods
(c) Markov Chain Monte Carlo (MCMC) methods
(d) Resampling methods

Teaching methods

Delivery typeNumberLength hoursStudent hours
Lecture321.0032.00
Practical11.001.00
Practical12.002.00
Private study hours115.00
Total Contact hours35.00
Total hours (100hr per 10 credits)150.00

Private study

Studying and revising of course material.
Completing of assignments and assessments.

Opportunities for Formative Feedback

Examples sheets.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
Report6-10 pages20.00
Total percentage (Assessment Coursework)20.00

There is no resit available for the coursework component of this module. If the module is failed, the coursework mark will be carried forward and added to the resit exam mark with the same weighting as listed above.


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 30 mins80.00
Total percentage (Assessment Exams)80.00

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 website

Last updated: 20/03/2018

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