Poster Session
Predicting and Comparing Medal Counts in the Summer and Winter Olympics
Location
Memorial Ballroom, Hall Campus Center
Access Type
Open Access
Entry Number
28
Start Date
4-10-2019 12:00 PM
End Date
4-10-2019 1:15 PM
College
Lynchburg College of Arts and Sciences
Department
Statistics
Abstract
This presentation uses variables unrelated to athletic ability to predict medal counts in the Summer and Winter Olympics. Furthermore, the two seasons of games are compared to see if certain factors are more important when winning a medal in one season than another. The variables used are GDP per capita in US dollars, a dummy variable measuring whether or not the country has a socialist history, and the latitude of the countries capital city. The response variable is medals. Since there are so many countries with zero medals during the games, a normal regression was not possible to run. After testing other models, we determined that a zero-inflated negative binomial regression would be the best model to use. This output was found using R. I found that wealthier countries tend to compete in the winter games than the summer, but with both groups more GDP increased the number of medals on average holding other variables constant. It is also noteworthy that countries located further north tend to do better in both games and that countries with a socialist history tend to not be in the zero-groups.
Faculty Mentor(s)
Dr. Bahaeddine Taoufik
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Predicting and Comparing Medal Counts in the Summer and Winter Olympics
Predicting and Comparing Medal Counts in the Summer and Winter Olympics
Memorial Ballroom, Hall Campus Center
This presentation uses variables unrelated to athletic ability to predict medal counts in the Summer and Winter Olympics. Furthermore, the two seasons of games are compared to see if certain factors are more important when winning a medal in one season than another. The variables used are GDP per capita in US dollars, a dummy variable measuring whether or not the country has a socialist history, and the latitude of the countries capital city. The response variable is medals. Since there are so many countries with zero medals during the games, a normal regression was not possible to run. After testing other models, we determined that a zero-inflated negative binomial regression would be the best model to use. This output was found using R. I found that wealthier countries tend to compete in the winter games than the summer, but with both groups more GDP increased the number of medals on average holding other variables constant. It is also noteworthy that countries located further north tend to do better in both games and that countries with a socialist history tend to not be in the zero-groups.