MAS31004 Statistics Individual Project: Explaining Olympic Performance
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MAS31004: Statistics Individual Project
Statistics Individual Project: Explaining Olympic Performance
1 Introduction
Every Olympic cycle there are debates in the media about the performance of the various competing nations. Examples concerning the 1992 Barcelona games are given in the Appendix. Some of the exchanges are light-hearted (for example, at the 2008 Beijing games, the Australians are alleged to have said that the British only win at sports in which they can sit down!), but financial support for the various sports is heavily dependent on ‘meeting expectations’ and the comments raise broader issues related to worldwide inequalities.
2 The Task
Consider the medal table from a recent Olympic Games (these are easily available online). What can be said about the relative achievements of the various nations and how these might be explained?
The exchange outlined in the Appendix gives some inspiration, but does not represent a direct template for your own study. You are advised to give specific consideration to: defining performance; identifying plausible explanatory variables; sourcing suitable data; handling data idiosyncrasies; selecting a suitable model; and appropriate interpretation.
You must produce a written report detailing all aspects of your investigation. The standard format discussed for reporting the results of a scientific investigation should be appropriate. There is no specific length limit.
You must also submit a file containing your R script and a file containing your data set (in original form, i.e. before any modifications made by your script).
3 What will be Judged?
The Individual Project is worth 30% of the marks for the module.
Many facets will contribute to the assessment of the Project. The report will be judged for both presentation (including style and detailed preparation) and content (description of problem, analysis–both what is attempted and ‘correctness’–and interpretation).
4 Required Submissions
❼ Store the R script documenting your analysis
❼ Name the file StatsScript-yourstudentnumber. R
❼ List the original data underpinning your analysis
❼ Name the file StatsData-yourstudentnumber. csv or Stats-yourstudentnumber. xlsx or ... as appropriate.
❼ Submit these two files to the Blackboard Assignment dropbox
❼ Produce a pdf document of your report.
❼ Name the file StatsReport-yourstudentnumber. pdf
❼ Submit this file to Blackboard Turnitin assignments
5 Deadlines
❼ Individual Project selections are to notified through Blackboard G10 folder link by 4pm on Friday 27 October 2023.
❼ Individual Projects are to be submitted by 4pm on Wednesday 13 December 2023 (week 12, sem 1).
Appendix
Attached are:
❼ a letter by Monojit Chatterji that appeared in The Independent newspaper on Sunday on 16 August 1992
❼ an extract from the article by Hugh Jones referred to by Monojit Chatterji
❼ an extract from the medals table from the 1992 Olympics
Chatterjee’s letter
I FOUND Hugh Jones’s piece (“Winners and Losers in Barcelona”, 9 August) fascinating. Measuring national performance by relating medal score to population size is obviously sensible. Who would have guessed that in these terms, the most successful nation would turn out to be Hungary?
The more interesting question raised by the article is: what accounts for the huge variation in performance across nations? Many would point to tradition, general health, training facilities, competitive structure, and so on. I carried out a simple exercise attempting to relate medal score per head of population to three explanatory factors - population (it is harder to spot talent in large countries), life expectancy (a reasonable measure of health) and per capita income (richer countries can afford better facilities). About half the cross-country variation in medal performance could be accounted for by these factors. Britain’s performance was wholly accounted for by the relationship between medal score per head and the collective strength of population size, life expectancy and per capita income. The surprises were Hungary, Cuba, Namibia, Bulgaria, South Korea,
Kenya and the Unified Team. All did much better than could be forecast on this basis. As for Britain, one cannot expect any changes in life expectancy or population by 1996. But if the recession continues, then watch for a slightly worse performance in Atlanta.
Monojit Chatterji,
University of Dundee
Jones extract
Meanwhile, step forward, Hungary – pound for pound the leading Olympic nation. For the table below we have awarded five points for a gold medal, three for a silver and one for a bronze, and then divided each country’s total number of points into their popula- tion. That gives the rating figure in the final column. The lower the figure the better the country’s performance.
POUND-FOR-POUND
Country Pop Pts Rating
Hungary |
10.45m |
98 |
0.107 |
Cuba |
10.58m |
81 |
0.131 |
New Zealand |
3.42m |
22 |
0.155 |
. . . |
. . . |
. . . |
. . . |
Thailand |
55.9m |
1 |
55.900 |
Philippines |
60.9m |
1 |
60.900 |
Pakistan |
114m |
1 |
114.000 |
*United Team/Commonwealth of Independent States (former Soviet republics) *Independent Participants (former Yugoslavia)
Some non-medal winning nations and their populations: India 844.32m, Pakistan 114m, Bangladesh 108m, Vietnam 65m, Egypt 56m, Burma 40.78m, Zaire 38.55m, Tanzania 25.09m, Uganda 18.44m, Portugal 10.39m.
Sample of medal data from 1992 Olympics
Country Gold Silver Bronze
United Team |
45 |
38 |
29 |
United States |
37 |
34 |
37 |
Germany |
33 |
21 |
28 |
. |
. |
. |
. |
. . |
. . |
. . |
. . |
Qatar |
0 |
0 |
1 |
Surinam |
0 |
0 |
1 |
Thailand |
0 |
0 |
1 |
(The Guardian, August 10, 1992)
2023-11-24