Poster or Presentation Title

Predicting and Comparing Medal Counts in the Summer and Winter Olympics

Student Author Information

Emmy YarmyFollow

Access Type

Open Access

Presentation Type

Oral Presentation

Start Date

April 2019

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)

Bahaeddine Taoufik

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Predicting and Comparing Medal Counts in the Summer and Winter Olympics

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Apr 10th, 10:15 AM

Predicting and Comparing Medal Counts in the Summer and Winter Olympics

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.