Use the data set in DATA_ASSIGNMENT, which includes information on number of medals won by each country in 2012 and 2016 in the Olympic Games held in London and Rio de Janeiro, respectively, and the characteristics of each country. Country ID is the country identifier. Year denotes the year when the Olympics games were held. Real GDP is the Real Gross Domestic Product of country in billions of dollars. Population is the number of people living in country in millions of people. Total Medals in the sum of gold, silver and bronze medals won by country. Host Country is a dummy variable that takes the value 1 if the country is hosting the Olympic Games and takes the value 0 if the country is not hosting the games. Planned Economy is a dummy variable that takes the value 1 if the country is a planned economy (or was a planned economy in the past), and 0 otherwise.

Present the descriptive statistics of the variables RealGDP, Population, Total Medals. Comment on the means and measures of dispersion (standard deviation, skewness, and kurtosis) of the variables.
Estimate the following simple regression model of total medals and real GDP.
Now estimate the following simple regression model with a level-log specification.
Now estimate a model that relates the total number of medals to the real GDP and population:
Now re-estimate the equation in (iv) but using the log of independent variables. That is, estimate the model,
Using the estimated model in (v), test whether the coefficient of log(realGDP) is greater than 3 at 5% level of significance.
Add the variable planned economy to the level-log equation in (v) and estimate the following model.
Test the overall significance of the model you estimated in part (vii) at 5% level of significance.
Suppose you want to test whether Host countries win more medals than other countries. Specify a regression model that will enable you to test such a hypothesis using the model in (vii) as a base. Test whether Host countries win more medals than non-host countries at the 5% level of significance.

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