MSc Applied Data Science and Statistics
MTHM504: Guidance on writing your thesis
Overview
Submission deadline: 10th December 2021
The written report contributes 70% towards the final mark of the module.
The written report should be between 30 and 40 pages in length (as an indication this should be
between 10,000 to 15,000 words) including figures, tables, and references. We strongly recommend
inserting tables and figures in the main report where you discuss them (rather than all at the end) for
ease of readability. Computer code should not appear in the main body of the report.
The report should be written concisely and explain the topic and context of your project. It should
provide details of the data and methodology you use and your results. You should present a discussion
of the main findings, highlighting any original aspects of the work and/or new findings.
Appendix
You may put additional material in an appendix. This might include tables and graphs if there too many
to fit into the main body of the report (you might want to consider limiting the number in the main body
of the report to around 10), but these must be clearly signposted/referenced within the main body of
the report.
You may also include detailed calculations, statistical analysis and computer code (all significant code
written as part of the project should be included within the appendix with detailed comments so that
examiners can easily follow the structure).
Feedback
If students require the supervisor to read a draft of the project (for purposes of feedback), then they
should allow at least two weeks before submission deadline.
Structure
The following is a suggested structure for the written report together with indicative percentages of the
number of pages to give an indication of possible lengths for the difference sections. You may use
alternative structures, but please remember that the structure you choose will have to allow you to
cover the points in the Overview given above.
• Presentation, formatting and logical flow (10%). Your report should be presented in a clear and
logical manner, with a clear narrative throughout. You should ensure that figure and table captions
are clear and explanatory and that the content within figures is large enough to read.
• Introduction, Aims, Background to the subject (10%). What are the main aims and objectives of the
project? Is it to prove a result, test a hypothesis, or develop techniques to solve a particular
problem? If developing a model, what are the key assumptions/limitations?
• Detailed review of literature on which project is based, Description of methodology, underlying
theory, etc. (35%). Provide details of previous attempts to look at this question - who has previously
written about this subject, what data and methods did they use, what were their conclusions? This
should include a discussion of how do the assumptions/methods used in article X compare to those
used in article Y?
• Description of data, analyses and results (35%). Where does you data come from? To include initial
summaries and initial data analyses. Application of your chosen methodology to your chosen data.
Presentation and description of results. How sensitive are your results to the method used/
assumptions made? How do your results relate to those in the literature, which may use different
methods? How would you extend your project given more time?
• Summary and discussion (10%). A summary of what you have done and a discussion of the results
you have found, putting them into the wider context of the aims of the project. What further
research do you think is needed? e.g. additional data, methodological developments.
Marking process
After submission, supervisors and a second marker mark the project reports (and the associated
presentations) independently. They will then agree a final mark. In case of large difference between
the two marks and/or no final agreement, the internal moderator assesses the project and helps in
reconciling the marks. The moderator also reviews all projects, and their marks, to ensure consistency
across projects. An academic from a different university, the external examiner, also reviews the project
marks and will view a sample of the projects to assure quality.
Academic honesty
Academic honesty means always giving full credit for any other people's contributions to our own
achievements (i.e. by full and correct referencing) and never falsifying the results of any research.
All written work, and research carried out must be your own (taking into account assistance from the
project supervisor). All literature and sources used must be cited appropriately. This includes any code
/packages developed by others that you have used.
For guidelines: see http://www.exeter.ac.uk/students/administration/rulesandregulations/ug-
pgt/academicmisconduct/
You should discuss any queries (e. g. how often and at what level of detail to cite particular papers and
books) with your supervisor or send an email to adss@exeter.ac.uk.
When submitting your final report, you will be asked to sign a declaration that the work is your own. All
project reports will be put through the plagiarism detection software Turnitin. The University takes
plagiarism and other forms of academic misconduct very seriously.



































































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