(K) The sensitivity = X X = and y = (L) The specificity = a a = and b = (M) The overall success rate of the logit model is (N) The false positive of the predicting equation is -. s = and t = (O) The false negative of the predicting equation is e = and f = (P) For every one unit change in gre, the logit of admission (versus non-admission) increases by (Q) For a one unit increase in gpa, the logit of being admitted to graduate school increases by (R) Having attended an undergraduate institution with rank of 1, versus an institution with a rank of 4, increases the logit of admission byand y = 1 = a va Block 1: Method = Enter Omnibus Tests of Model Coefficients Chi-square df Sig. Step 1 Step 41.459 .000 en Block 41.459 .000 ren Model 41.459 000 Model Summary -2 Log Cox & Snell R Nagelkerke R Step likelihood Square Square 458.5173 .098 .138 a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001. (J) The value of the G statistic is , and indicates that the three predictor variables Classification Table Predicted admit Percentage Observed Correct Step 1 admit 254 93.0 23.6 Overall Percentage 71 . a. The cut value is .500 Variables in the Equation S.E Wald sig. Exp (B) Step 1 a gre 002 4.284 .038 1.002 gpa .804 332 5.872 .015 2.235 rank 20.895 m .000 rank(1) 1.551 418 13.787 .000 4.718 rank(2) 876 367 5.706 .017 2.401 rank(3) .211 393 .289 .591 1.235 Constant -5.541 1.138 23.709 000 .004 a. Variable(s) entered on step 1: gre, gpa, rank