What can predict how much a motion picture will make? The statistics computed below use data from a number of recent releases that includes the USGross (in $), the Budget ($), the Run Tlme (minutes), and the average number of stars awarded by reviewers. Complete parts a and b below. @ Click the icon to view a subsample of data on recent movie releases. @ Click the icon to view the regression statistics. a) What is the R2 for this regression? What does it mean? Choose the correct explanation of R2 below, and ll in your calculated value of R2, l.' A- Accounting for the number of predictors, about % of the variation in USGross is accounted for by the least squares regression on Budget, Run Time, and Stars. C' B- The probability that USGross is greater than the least squares regression on Budget, Run Time, and Stars is %. C' 0- About % of the variation in USGross is accounted for by the least squares regression on Budget, Run Tlme, and Stars, 'Z' 0- The least squares regression on Budget, Run Time, and Stars will accurately predict USGross % of the time, Subsample of Data on Recent Movie Releases b) Why is the "Adjusted R Square" in the table different from the "R Square"? - Adjusted R2 uses only the signicant predictors with small P-values, so it differs from R2, which does not. B Movie USGross (SM) Budget (SM) Run Time (minutes) Summer Blockbuster 41 .451038 35 100 - Adjusted R2 does not account for the number of predictors, so it differs from R2, which does. Gripping Drama 56.099423 30 107 Comic Relief 31457506 40 109 , Adjusted Rz accounts for the number of predictors, so it differs from R2, which does not. - Adjusted R2 excludes the predictors with small P-values, so it differs from R2, which does not. Regression Statistics Dependent variable is: USGross (35) R squared = 47.4% R squared (adjusted) = 46.0% s = 46.15 with 120 - 4 =116 degrees of freedom ariable Coef SE(Coef) t P-Val Intercept - 229462 2404 - 0.955 0.3416 Budget ($) 1.11779 0.1233 9.07