MAT022 Foundations of Statistics and Data Science
Summative Assessment 2019/20
Summative assessment for the module is by means of a single report on your statistical analysis
of data related to the decathlon, a combined event in athletics where an athlete’s performance in
ten track-and-field events is determined by a points system.
This form of assessment has been chosen because, as professional statisticians and data scientists,
you will often be asked to investigate a data set and report on whether it contains anything useful
the summer.
Assessment type Weight Max. length Format Deadline
Report 100% 10 pages PDF Friday 10 January 2020
Your report will be assessed according to how well you are able to
• analyse the data set, 40%
• interpret the results of your analysis, and 30%
• present the results of your analysis and interpretation of the data set. 30%
You are free to use any statistical software package to conduct your analysis (e.g. R or SPSS), and
any word processing software to prepare your report (e.g. LATEX or Microsoft Word).
1 The data
You are asked to write a report on data related to the decathlon. This is a combined event in
athletics where an athlete’s performance in ten track-and-field events is determined based on a
points system. The winner of the competition is the athlete who has the most points after all ten
events have been completed.
The basic decathlon data set records the performance of elite decathletes over the period from
1986 to 2006, and has been widely studied. The set consists of 7968 observations on 24 variables
as shown in Table 1, and is available on Learning Central as a .csv file.
The basic data set is also included with the GDAdata package in R and can be loaded as follows.
> summary(Decathlon)
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MAT022 Foundations of Statistics and Data Science Summative Assessment 2019/20
Variable Description
Totalpoints Total points achieved over all 10 events
DecathleteName Decathlete’s name
Nationality Decathlete’s nationality
m100 Time for the 100 metres (secs)
Longjump Distance jumped (metres)
Shotput Distance putting the shot (metres)
Highjump Height jumped (metres)
m400 Time for the 400 metres (secs)
m110hurdles Time for the 110 metres hurdles (secs)
Discus Distance throwing the discus (metres)
Polevault Height achieved (metres)
Javelin Distance throwing the javelin (metres)
m1500 Time for the 1500 metres (secs)
yearEvent Year of performance
P100m Points for performance in 100 metres
Plj Points for performance in long jump
Psp Points for performance in putting the shot
Phj Points for performance in high jump
P400m Points for performance in 400 metres
P110h Points for performance in 110 metres hurdles
Ppv Points for performance in pole vault
Pdt Points for performance in discus
Pjt Points for performance in javelin
P1500 Points for performance in 1500 metres
Table 1: The basic decathlon data set
To expand your analysis of the decathlon you are encouraged to find additional sources of data,
making sure that the provenance of the sources are evaluated and discussed in your report. You
are also encouraged to explore additional statistical methods that have not been discussed in the
lectures and notebooks, making sure that you provide a brief description of these methods along
with references to the relevant literature. You can nevertheless base your study entirely on the
data set provided, it has plenty of scope for you to produce an excellent report.
2 The report
The ability to write clearly and concisely is an important professional competence. To encourage
writing that is brief and to the point, your reports are limited to a maximum of 10 pages. It
is often far more difficult to express yourself in 100 words than in 1000 words, especially when
you have a lot to say, so please do not underestimate the challenge posed by this restriction. The
modest page limit will also encourage you to be selective in the results you choose to present.
A suggested structure for your report is shown in Table 2. Note that the title page, abstract, table
of contents and list of references will not contribute towards the page count.
• The title page should contain the title of your report, your name and student number, and
the date on which your report was completed.
• The abstract should contain a short summary of the report and its main conclusions.
• The table of contents should list the number and title of each section against the number
of the page on which the section begins.
• The introduction should consist of a few short paragraphs, describing the purpose of the
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MAT022 Foundations of Statistics and Data Science Summative Assessment 2019/20
Title 1 page
Abstract 100 words
1. Introduction 1/2 page
2. Background 1/2 – 1 page
3. (descriptive analysis) 1 – 2 pages
4. (inferential analysis) 2 – 3 pages
5. (inferential analysis) 2 – 3 pages
6. Conclusion 1/2 page
References –
Appendices 2 pages max.
Table 2: Report structure
report and providing a brief outline of its contents.
• The background chapter should include a brief review of any relevant literature, and provide
a context for the work presented in the report.
• The report should contain a relatively short section on a descriptive analysis of the data,
with a title chosen to reflect what the section contains.
• The main part of the report should consist of one or more sections on an inferential analysis
of the data. Here you should formulate hypotheses, conduct statistical tests and discuss the
results of these tests. The titles of these sections should reflect what the sections contain.
• The conclusion should consist of a few short paragraphs, providing a summary of the report
and a brief outline of some ideas for future work.
• Any references should be typeset using the Harvard referencing style.
• The report may contain a single appendix for large figures and tables.
3 Assessment criteria
Detailed assessment criteria are shown in Table 3.
4 Guidelines for writing reports
The golden rule when writing is to always think of the reader. For scientific reports, readers
will typically want to read something interesting and to learn something in the process.
What do we mean by interesting?
Not interesting The average exam marks of statistics and data science students.
Quite interesting The average marks of male students, the average marks of female students, and
the results of a test of whether any difference is statistically significant.
Very interesting The average marks of male students, the average marks of female students, a
statistical test of whether any difference is significant, and some speculation
about why there is a significant difference, or alternatively why there is not.
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MAT022 Foundations of Statistics and Data Science Summative Assessment 2019/20
Level Analysis
(40%)
Discussion
(30%)
Presentation
(30%)
Distinction
(70–100)
Hypotheses are interesting and original.
Methods are appropriate and applied
carefully and precisely.
An interesting descriptive analysis is included
and reported correctly.
Inferences are valid
and supported by evidence. Original and
interesting conclusions
are articulated. There
is some shrewd speculation about possible
causal factors.
A high standard of
writing is maintained
throughout. The narrative is clear, coherent, eloquent and refined. Figures and tables are used creatively.
Merit
(60–69)
Hypotheses are formulated correctly. Methods are appropriate and
applied correctly. A
moderately interesting
descriptive analysis is
included and reported
correctly.
Inferences are valid and
supported by evidence.
Interesting conclusions
are articulated. There
is some speculation
factors.
A good standard or
writing is maintained
throughout. The narrative is clear and coherent. Figures and tables are used to illustrate the narrative.
Pass
(50–59)
Hypotheses are formulated correctly. Methods are applied correctly for the most part.
A descriptive analysis is
included and reported
correctly.
Inferences are mostly
valid and supported
by some evidence.
Some relatively interesting conclusions are
articulated.
An acceptable standard
of writing is maintained
throughout. The narrative is lacklusture
and sometimes unclear.
Figures and tables do
not always illustrate
the narrative.
Fail
(0–49)
The analysis is bland
and almost entirely descriptive.
Inferences are invalid or
not supported by evidence. There is little of
any interest.
The report is poorly
written. The narrative
is disjointed and hard
to follow.
Table 3: Assessment criteria
Audience. The target audience for your report is this year’s cohort students on the Foundations
of Statistics and Data Science module, so you can assume that your readers are familiar with the
methods and terminology established within the lectures and notebooks. If you choose to use
methods that have not been covered in lectures, you must ensure that any new terms are properly
defined, and references to the relevant literature included.
Analysis. The reader shoud be satisfied that you have performed your analysis correctly, and in
particular that you have verified the conditions that are necessary to apply the various methods.
Your methods should be introduced with a brief summary of their main features, but technical
details should not be discussed at length, although you might consider providing the interested
reader with references to the relevant literature.
Navigation. Do not assume that the reader will read the report from start to finish, as one might
read a novel. Reports should be made easy to navigate using numbered sections and subsections
together with cross-referencing. Once you have written a first draft, it will need careful editing
before it becomes a coherent and polished report. This stage always takes longer than you think!
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MAT022 Foundations of Statistics and Data Science Summative Assessment 2019/20
Scientific writing. For scientific reports we aim for a style of writing that is clear and concise.
Make sure that sentences are unambiguous and that a good standard of writing is maintained
throughout the report.
• Sections should not start abruptly with the subject matter, but rather with an introductory
sentence or short paragraph. Sections should also end with concluding sentence or short
paragraph.
• All figures and tables must be numbered and have captions. Figures or tables that are not
mentioned at least once in the text should not be included.
• A qualified statement is one that express some level of uncertainty about its own accuracy,
and should always be used when drawing conclusions from the results of a statistical analysis,
and especially when speculating about possible causal factors. Common phrases that indicate
qualified statements include “This suggests that …”, “It appears that …”, “We might conclude
that …”, “There is some evidence to indicate …” and so on.
• Be careful with florid turns of phrase, whatever their merit as literature. Academic reports
are primarily a way of communicating information, and care must be taken to accommodate
readers from diverse backgrounds, including non-native English speakers. Reports should
use everyday words and simple grammatical structures as far as possible.
Plagiarism
The basic decathlon data set has been widely studied and you will find plenty of material online
incorporating it into your work without full acknowledgement. The need to acknowledge others’
work applies not only to text, but also to computer code, figures, tables etc. You must also attribute
analysed by the TurnitIn software, and any report in which plagiarism is detected will receive a
mark of zero.
Please submit your report via Learning Central on or before Friday 10 January 2020.
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