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Exam (elaborations)

Mathematics of Data Analytics (MATH1146)

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QUESTION OF THE ASSIGNMENT

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MATH1146 (2020/21) Mathematics of Data Analytics Contribution: 40% of module

Course Leader: MATH1146 Data Visualisation Deadline Date: Thursday
Tony Mann Assignment 14/01/2021

This coursework will be marked anonymously
YOU MUST NOT PUT ANY INDICATION OF YOUR IDENTITY IN YOUR SUBMISSION

This coursework should take an average student up-to-date with tutorial work about 20 hours

Feedback and marks are normally available within 15 working days of the coursework deadline

Learning Outcomes:
2 Apply the regulations and ethical considerations surrounding data protection, data mining and
warehousing.
4 Critically evaluate different data visualisation tools and techniques and present data in a variety of
ways to aid senior management in decision making.
5 Explain the need for cleaning data and apply a variety of techniques for this purpose.

Plagiarism is presenting somebody else's work as your own. It includes: copying information
directly from the Web or books without referencing the material; submitting joint coursework as
an individual effort; copying another student's coursework; stealing coursework from another
student and submitting it as your own work. Suspected plagiarism will be investigated and if
found to have occurred will be dealt with according to the procedures set down by the
University. Please see your student handbook for further details of what is / isn't plagiarism.

All material copied or amended from any source (e.g. internet, books) must be referenced correctly
according to the Harvard reference style.

Your work will be submitted for plagiarism checking. Any attempt to bypass our plagiarism
detection systems may be treated as a severe Assessment Offence.


Coursework Submission Requirements

• An electronic copy of your work for this coursework must be fully uploaded on the Deadline
Date of Thursday 14/01/2021 using the link on the coursework Moodle page for MATH1146.
• For this coursework you must submit a single PDF document, with an additional PDF
containing the poster if you cannot combine it with your other answers.
• There are limits on the file size (see the relevant course Moodle page).
• Make sure that any files you upload are virus-free and not protected by a password or
corrupted otherwise they will be treated as null submissions.
• You must NOT submit a paper copy of this coursework.
• All courseworks must be submitted as above. Under no circumstances can they be accepted
by academic staff

The University website has details of the current Coursework Regulations, including details of
penalties for late submission, procedures for Extenuating Circumstances, and penalties for
Assessment Offences. See http://www2.gre.ac.uk/current-students/regs




Page 1

, Mathematics of Data Analytics - Coursework 2 (Data Visualisation Assignment)
Deliverables and Data:
You should attempt all four questions. Where appropriate you are expected to research
beyond lecture material and reference your sources using the Harvard referencing system.
The marking rubric for this assignment is given at the end of the specification.

Answers should be submitted as a PDF. The poster should be created as a PowerPoint slide
and then the final version should be saved as a PDF and uploaded in this format. A template
is provided on Moodle (which provides the correct dimensions for the poster but is otherwise
blank) – there are separate templates for landscape and portrait formats and you may choose
whichever format you prefer

The data for question 1 is available on the Moodle page for this course. You will need to open
the data spreadsheet and input your University ID number to generate your data. (Do not
worry if it takes a long time to generate the data.) You will then need to save the resulting
Excel file. The data is specific to your ID number so do make sure you enter your number
correctly so that you use the correct data which is unique to you. Failure to use the correct
data may result in you losing marks.




Page 2

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Uploaded on
August 31, 2021
Number of pages
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Written in
2021/2022
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