Regression Run 8.12: Source I df MS Number of obs = F( 6, 58)= 15.87 Prob >F R-s
ID: 3266251 • Letter: R
Question
Regression Run 8.12: Source I df MS Number of obs = F( 6, 58)= 15.87 Prob >F R-squared Adj R-squared 0.582 2 Root MSE 65 6 242718.383 Residual887295.854 58 15298.2044 Model 1456310.3 0 . 0000 - 0.6214 Total 2343606.15 64 36618.8462 123 . 69 = SAT I Coef. Std. Err (95% Conf. Interval] GPA 129.8782 37.48974 APMATH76.41832 40.55854 APENG 92.42253 44.71331 ESL I -34.01275 35.01006 GEND108.1642 31.08865 204.9221 157.6051 181.926 36.06751 170.3949 PREP -31.72391 35.52388 -0.89 0.376-102.832739.38488 57.8717 3.46 0.001 1.88 0.065 2.07 0.043 0.970.335 3.48 0.001 54.83437 -4.768418 2.919109 104.093 5.93352 cons 531.4692 113.1041 4.70 0.000 05.0668Explanation / Answer
The regression model is highly significant with F(6, 58)=15.87, p=0.0000<0.001. R-square is 0.6214 which means that all the predictors taken together explained 62.14% of the variability in SAT score.
The estimated regression model is
SAT=531.47 + 129.88 GPA+76.42 APMATH+92.42 APENG-34.01 ESL
+108.16 GEND -31.72 PREP
GPA is a significant predictor of SAT, p=0.001<0.05. Corresponding to unit increase in GPA there is on an average an increase of 129.88 in SAT, holding other predictors fixed.
APMATH is not a significant predictor of SAT, p=0.065>0.05
APENG is a significant predictor of SAT, p=0.043<0.05. Corresponding to unit increase in APENG there is on an average an increase of 92.42 in SAT, holding other predictors fixed.
ESL is not a significant predictor of SAT, p=0.335>0.05.
GEND is a significant predictor of SAT, p=0.001<0.05. Corresponding to unit increase in GEND there is on an average an increase of 108.16 in SAT, holding other predictors fixed.
PREP is not a significant predictor of SAT, p=0.376>0.05.