A dean of a business school has fit a regression model to predict college GPA based on a i on a student's SAI score (SAT_Score), the percentile at which the student graduated high school (HS_Percentile) (for instance, graduating 4th in a class of 500 implies that 496 other students are at or below that student, so the percentile is 496/500 x 100 = 99), and the total college hours the student has accumulated (Total_Hours). The regression results are shown below. What would be the estimated mean GPA for a student with an SAT score of 1120, a high school percentile rank of 84, and total accumulated hours of 33? In the calculation and answer, use three decimal places. Regression Statistics Multiple R 0.53292259 R Square 0.284006487 Adjusted R Square 0.283486772 Standard Error 0.557515239 Observations 4137 ANOVA df SS MS F Significance F Regression 3 509.5632068 169.8544 546.4662 4.0431E-299 Residual 4133 1284.632457 0.310823 Total 4136 1794. 195664 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -0.042678047 0.070175203 -0.60816 0.543112 -0. 180259209 0.094903114 SAT_Score 0.001491364 6.48677E-05 22.99086 3.6E-110 0.001364189 0.00161854 HS_Percentile 0.013087778 0.000548313 23.86919 4.5E-118 0.01201279 0.014162766 Total Hours ... .-.-. 0.001926045 0.000246629 7.809486 7.23E-15 0.001442519 0.00240957