Question 19 2.5 Exhibit 6 contains the following regression model: Bearing Acreage = F(average grower prices, HLB cases, marketing) Why is is preferable to use the adjusted R square for goodness of fit? it minimizes the sum of squares due to regression it inflates prediction errors it is calculated the same way as for the SLR (SSR/SST) it accounts for the additional independent variables Exhibit 6: Florida Bearing Acreage as a function of average grower price, HLB cases, and marketing budget Regression Statistics Multiple R 0.9700 R Square 0.9300 Adjusted R Square 0.9000 Standard Error 10.3800 Observations 9 ANOVA df SS MS Regression 3 7,711.13 2,570.38 Residual 5 538.64 107.73 Total 8 8,249.76 Coefficients Standard Error t Stat 357.37 52.29 6.83 Intercept -5.17 3.69 -1.4 Average Grower Return ($/box) 1.17 1.45 Confirmed HLB (count) 1.05 1.72 Marketing Budget (mil $) 3 9 0 51 52 1.69 53 1.81 54