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Suppose That You Regress the Total Number of Medals That

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Suppose that you regress the total number of medals that a country won in the 2008 Olympics on GDP per capita and that you get the results in Figure 4.2. SUMMARY OUTPUT

 Regression Statistics  Mutiple R 0.193666659 R Square 0.037506775 Adjusted R Square 0.027881842 Standard Error 17.8035921 Observations 102\begin{array}{lc}\hline \text { Regression Statistics } & \\\hline \text { Mutiple R } & 0.193666659 \\\text { R Square } & 0.037506775 \\\text { Adjusted R Square } & 0.027881842 \\\text { Standard Error } & 17.8035921 \\\text { Observations } & 102 \\\hline\end{array}

 ANOVA  if SS MS F Significance F Regression 11235.1716331235.1716333.8968351880.05113579 Residual 10031696.78915316.9678915 Total 10132931.96078\begin{array}{l}\text { ANOVA }\\\begin{array}{lccccc}\hline & \text { if } & S S & \text { MS } & F & \text { Significance } F \\\hline \text { Regression } & 1 & 1235.171633 & 1235.171633 & 3.896835188 & 0.05113579 \\\text { Residual } & 100 & 31696.78915 & 316.9678915 & & \\\text { Total } & 101 & 32931.96078 & & & \\\hline\end{array}\end{array}

 Coefficients  Standard Error t Stat  P-value  Lower 95% Upper 95% Intercept 6.07922.30792.63410.00981.500510.6580 GDP Per Capita (Thousands) 0.15530.07871.97400.05110.00080.3113\begin{array}{lcccccc}\hline & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & \text { P-value } & \text { Lower } 95 \% & \text { Upper } 95 \% \\\hline \text { Intercept } & 6.0792 & 2.3079 & 2.6341 & 0.0098 & 1.5005 & 10.6580 \\\text { GDP Per Capita (Thousands) } & 0.1553 & 0.0787 & 1.9740 & 0.0511 & -0.0008 & 0.3113 \\\hline\end{array}
Figure 4.24.2
How would you interpret these results? What would you say about the Goodness-of-Fit of the regression? Explain.
What would be the predicted number of medals for a country with a GDP per capita of $25,000? $40,000? Show your work.


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