Many countries, especially those in Europe, have significant gold holdings. But, many of these countries also have massive debts. The following data show the total value of gold holdings in billions of U.S. dollars and the debt as a percentage of the gross domestic product for nine countries (WordPress and Trading Economics websites, February 24, 2012). Country Gold Value Debt China 63 17.7 France 146 81.7 Germany 203 83.2 Indonesia 33 69.2 Italy 147 119 Netherlands 36 63.7 Russia 50 9.9 Switzerland 62 55 U.S. 487 93.2       c. Using the entire data set, develop the estimated regression equation that can be used to predict the debt of a country given the total value of its gold holdings. d. Use residual analysis to determine whether any outliers or influential observations are present. e. Suppose that after looking at the scatter diagram in part (a) that you were able to visually identify what appears to be an influential observation. Drop this observation from the data set and fit an estimated regression equation to the remaining data. Compare the estimated slope for the new estimated regression equation to the estimated slope obtained in part (c). Does this approach confirm the conclusion you reached in part (d)? Explain.

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Many countries, especially those in Europe, have significant gold holdings. But, many of these countries also have massive debts. The following data show the total value of gold holdings in billions of U.S. dollars and the debt as a percentage of the gross domestic product for nine countries (WordPress and Trading Economics websites, February 24, 2012).

Country Gold Value Debt
China 63 17.7
France 146 81.7
Germany 203 83.2
Indonesia 33 69.2
Italy 147 119
Netherlands 36 63.7
Russia 50 9.9
Switzerland 62 55
U.S. 487 93.2
     

c. Using the entire data set, develop the estimated regression equation that can be used to predict the debt of a country given the total value of its gold holdings.

d. Use residual analysis to determine whether any outliers or influential observations are present.

e. Suppose that after looking at the scatter diagram in part (a) that you were able to visually identify what appears to be an influential observation. Drop this observation from the data set and fit an estimated regression equation to the remaining data. Compare the estimated slope for the new estimated regression equation to the estimated slope obtained in part (c). Does this approach confirm the conclusion you reached in part (d)? Explain.

 

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