Question

Which of the following is true of the R-squared statistic?

It is the standard error of the coefficient associated with an independent variable.
It measures the slope of the regression equation.
It measures the proportion of the variation of the dependent variable explained by the multiple-regression equation.
It measures the total variation in the dependent variable induced by changes in the explanatory variables.
It measures the proportion of the variation of the dependent variable left unexplained by the multiple-regression equation.

Suppose that the “goodness of fit” of an equation is nearly perfect. What is the value of the R2 statistic in this case?
Very close to −1
Very close to positive infinity
Very close to 0
Very close to +1
Very close to .5

Calculate the degrees of freedom in a regression equation if the number of observations is 6 and the number of coefficients in the equation is 2.
12
8
0.33
4
3

Computing the F-statistic allows one to:
predict the increased explanation of any additional variables that might be included.
measure the degrees of freedom in the regression.
measure the forecasting accuracy of the regression equation.
test the overall statistical significance of the regression equation.
determine which variable contributes the most explanatory power to the regression.