Is there a correlation between GDP and the marathon time male athletes received in the 2016 Rio Olympics?
The Role of GDP in Athlete’s Performances in Olympic Marathons
Intro and Hypothesis: This project will look at GDP statistics of all the countries of the 140 finishers in the 2016 Olympic marathon. Using those statistics and numbers, the χ^2 test of independents will be calculated. The mean of the GDP levels and marathon finish times will be calculated to determine the average finish time and GDP level in the data pool to know and understand where a country is located. It is expected that there will be a minor correlation. It is difficult to know for sure whether a country’s Gross Domestic Product will have a direct …show more content…
This is important because the GDP correlates with the same year that the Olympics took place. I used the times and places of individuals along with their countries GDP. I took the 140 finishers and eliminated the 15 people who did not finish from my data. I came up with this project because I am currently on the track team and I wondered if there was a correlation of a runner’s marathon time with the runner’s GDP. I wanted to determine if placing and times were determined by talent or if runners were more likely to do better with a higher GDP because a higher GDP means more resources of all sorts and the opposite for a country with a lower GDP. I put my data that was taken from the 2016 Olympics and the 2016 Countries Gross Domestic Product on a graph but the graph visually showed no correlation so I proceeded to calculate the χ^2 test of independence. Before testing however, I added up all of the marathon times and GDP levels from my appendices and then divided by the 140 finish times to calculate the mean to find the average marathon time and GDP level. (See chart below)
Next I had to place my data on a contingency table to organize the data in different categories to be able to calculate the Chi Squared test. Contingency Table
GDP 2:08:00 - 2:17:00 2:17:01 - 2:26:00 2:26:01 - 2:47:00 Sum
0-100 14 27 16 57
101-1000 5 22 19 46 …show more content…
The χ^2 test indicated that there was no correlation between GDP. Perhaps running is just talent based but certainly more data is necessary to fully conclude that GDP and marathon times are independent.
If I were to do this project again, I think that I would want to test data from other Olympics as well as test the correlation of runner’s times with the HDI (Human Development Index). The HDI measures how developed humans are using life expectancy, education, and per capita income. This may be a way to get even better results. I also only tested male athletes and perhaps testing both male and female athletes might give better results as well. I also think that even though I had 140 runners to get completely accurate results, more points of data are necessary.
Appendices/Bibliography:
Olympic Marathon Times: "Feyisa LILESA." International Olympic Committee. N.p., 29 Nov. 2016. Web.
The Role of GDP in Athlete’s Performances in Olympic Marathons
Intro and Hypothesis: This project will look at GDP statistics of all the countries of the 140 finishers in the 2016 Olympic marathon. Using those statistics and numbers, the χ^2 test of independents will be calculated. The mean of the GDP levels and marathon finish times will be calculated to determine the average finish time and GDP level in the data pool to know and understand where a country is located. It is expected that there will be a minor correlation. It is difficult to know for sure whether a country’s Gross Domestic Product will have a direct …show more content…
This is important because the GDP correlates with the same year that the Olympics took place. I used the times and places of individuals along with their countries GDP. I took the 140 finishers and eliminated the 15 people who did not finish from my data. I came up with this project because I am currently on the track team and I wondered if there was a correlation of a runner’s marathon time with the runner’s GDP. I wanted to determine if placing and times were determined by talent or if runners were more likely to do better with a higher GDP because a higher GDP means more resources of all sorts and the opposite for a country with a lower GDP. I put my data that was taken from the 2016 Olympics and the 2016 Countries Gross Domestic Product on a graph but the graph visually showed no correlation so I proceeded to calculate the χ^2 test of independence. Before testing however, I added up all of the marathon times and GDP levels from my appendices and then divided by the 140 finish times to calculate the mean to find the average marathon time and GDP level. (See chart below)
Next I had to place my data on a contingency table to organize the data in different categories to be able to calculate the Chi Squared test. Contingency Table
GDP 2:08:00 - 2:17:00 2:17:01 - 2:26:00 2:26:01 - 2:47:00 Sum
0-100 14 27 16 57
101-1000 5 22 19 46 …show more content…
The χ^2 test indicated that there was no correlation between GDP. Perhaps running is just talent based but certainly more data is necessary to fully conclude that GDP and marathon times are independent.
If I were to do this project again, I think that I would want to test data from other Olympics as well as test the correlation of runner’s times with the HDI (Human Development Index). The HDI measures how developed humans are using life expectancy, education, and per capita income. This may be a way to get even better results. I also only tested male athletes and perhaps testing both male and female athletes might give better results as well. I also think that even though I had 140 runners to get completely accurate results, more points of data are necessary.
Appendices/Bibliography:
Olympic Marathon Times: "Feyisa LILESA." International Olympic Committee. N.p., 29 Nov. 2016. Web.