A dataset of 400 prospective students has a binary response outcome variable called admit, which is equal to 1 if the individual was admitted to graduate school, and 0 otherwise. There are three predictor variables: gre, gpa, and rank. gre and gpa are continuous quantitative variables. The qualitative variable undergraduate rank takes on the values 1 through 4. Institutions with a rank of 1 have the highest prestige, while those with a rank of 4 have the lowest. Schools with a rank of 4 act as the control group. SPSS gives the following analyses for the logistic regression model: Classification Table .b Predicted admit Percentage Observed 1 Correct Step 0 admit 273 100.0 127 Overall Percentage 68:3 a Constant is included In the model b. The cut value is .500 Variables in the Equation B S.E. Wald di Sig Exp(B) Step 0 Constant - 765 $107 50 764 000 .465 (1) Exp(B) = .465, and is equal to both e and the fraction The numeric values z= X= , and y =