As part of a study at a large university, data were collected on n= 224 freshmen computer science (CS) majors in a particular year. The researchers were interested in modeling y, a student's grade point average (GPA) after three semesters, as a function of the following independent variables (recorded at the time the students enrolled in the university): X1 = average high school grade in mathematics (HSM) × 2 = average high school grade in science (HSS) X 3 = average high school grade in English (HSE) XA = SAT mathematics score (SATM) X5 = SAT verbal score (SATV) A first-order model was fit to the data with the following results: SOURCE DF MS F VALUE PROB>F S MODEL 28.64 5.73 11.69 .0001 ERROR 218 106.82 0.49 TOTAL 223 135.46 ROOT MSE DEP MEAN 0.700 4.635 R-SQUARE ADJ R-SQ 0.211 0.193 I FOR O ERROR PARAMETER =0 PROB>ITI PARAMETER STANDARD VARIABLE ESTIMATE INTERCEPT 0.0001 0.0003 0.3432 2.327 0.039 5.817 X1 (HSM) X2 (HSS) X3 (HSE) 0.146 0.037 3.718 0.036 0.038 0.950 0. 1637 0. 1702 0.4915 Test to determine if the model is adequate for predicting GPA. Use a = .01. 0.055 0.00094 -0.00041 0.040 1.397 X4 (SATM) X5 (SATV) 0.00068 0.0059 1.376 -0.689