MA981-7-AP-CO:
Dissertation

The details
2023/24
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Autumn & Spring
Postgraduate: Level 7
Current
Thursday 05 October 2023
Sunday 14 January 2024
60
07 November 2023

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC G305JS Applied Data Science,
MSC G306JS Data Science and its Applications

Module description

Students will be provided with a list of dissertation titles or topics proposed by members of staff. It may also be possible to propose a topic of your own, provided a member of staff agrees it is of a suitable standard and is able to supervise it.


We hope there will be a mechanism for expressing preferences about which topic to do, and that this will be reflected in the allocation of topics to candidates. However, it must be pointed out that the exact nature of the procedure cannot be guaranteed because of staff numbers and availability, staff interests etc.

Module aims

The aim of this module is:



  • To write a dissertation based on an independently developed research project, under the supervision of an allocated supervisor.

Module learning outcomes

Students are expected to write a dissertation with the following aspects in mind:



  1. Clarity and coherence: students should understand the ideas involved in the subject at an appropriate level. In a project developing some piece of theory, the work should develop the theory in a logical order, with clear definitions and explanation of how these ideas could be useful in practice. In a project applying existing mathematical theories/methods/models to a practical question/data, a clear explanation of why and how these theories/methods/models are applied in the practical example(s) should be included.

  2. At a suitable level of difficulty, depth and breadth of ideas expressed. Students are expected to have sufficient depth of understanding for an MSc dissertation – in particular, the material should have little or no overlap with that in students’ course lectures. Original material or insights are not required, but are very welcome, and often students are expected to give different examples than those in original sources.

  3. In good quality of English and word processing. Mathematical formulas, figures and tables should be presented clearly and accurately in the dissertation. The resources, such as books, papers, online resources should be properly cited and listed as references.

  4. Include a section of literature review in the area of the project.

Module information

No additional information available.

Learning and teaching methods

No information available.

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Dissertation  24/11/2023   

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

100 per cent Coursework Mark

Reassessment

100 per cent Coursework Mark

Module supervisor and teaching staff
Dr Vasileios Giagos, email: v.giagos@essex.ac.uk.
Various
v.giagos@essex.ac.uk

 

Availability
No
No
No

External examiner

Dr Yinghui Wei
University of Plymouth
Resources
Available via Moodle
No lecture recording information available for this module.

 

Further information

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