Project - MA867

Location Term Level Credits (ECTS) Current Convenor 2019-20
(version 3)
View Timetable
7 60 (30)







The module enables students to undertake an independent piece of work in a particular area of statistics, or statistical finance/financial econometrics and to write a coherent account of the material.

There is no specific syllabus for this module.

A list of possible topics, together with names of Staff willing to supervise these projects, will be circulated to students in the autumn term. A broad range of projectsis available, encompassing both practical data analysis and more methodological work, although projects that are primarily theoretical will typically have obvious practical applications. Students then choose a topic after consultation and agreement with the relevant member of staff. This is done early in the spring term and some preliminary work is done during the spring term, leading to a short presentation at the end of that term. The main part of the project is then undertaken after the examinations in May.


This module appears in:

Contact hours

10 hours

Method of assessment

95% Project, 5% Coursework

Indicative reading

There is no general reading list for this module. Literature relevant to specific project topics will be recommended by individual supervisors.

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes. On successfully completing the module students will be able to:

1 demonstrate the relationship of the material to background material and to more advanced material;
2 write a coherent account of an area of Statistics, with particular reference to applications in Finance, if appropriate;
3 perform statistical analyses that show the depth of student understanding of the statistical methods relevant to the topic. This is especially the case for students of Statistics; students of Statistics in Finance may alternatively have demonstrated understanding of the importance of Statistics to Finance. These issues will depend on the topic studied;
4 present analyses and drawn conclusions with clarity and accuracy;
5 demonstrate understanding of theoretical and practical aspects of analysing statistical data. This is especially true for MSc students in Statistics.

The intended generic learning outcomes. On successfully completing the module students will be able to:

1 apply a logical, mathematical approach to solving complex problems, at an advanced level;
2 work with relatively little guidance, and be able to exercise initiative;
3 utilise advanced organisational, computer and study skills, and be able to adapt them to new situations;
4 use scientific word processing software, such as LaTex, to present their dissertation;
5 produce a dissertation that effectively communicates the material to the reader;
6 demonstrate an ability to evaluate research work critically;
7 select material from source texts, either recommended to or found by the student.

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.