To evaluate a graduate program, data collected form the admission department like GRE score, undergraduate GPA and undergraduate program ranking (prestige). The dependent (response) variable is a binary categorical variable: admit/don't admit. Please define the method use to get the following SAS output, Interpret all the sections of the output. Also, explain how to obtain percent concordant, percent discordant and percent tied pairs. (25) C:\dat -\logit ADMIT Written by SAS Data Set Response Variable Number of Response Levels Model Optimization Technique binary logit Fisher's scoring Number of Observations Read Number of Observations Used Response Profile 400 400 Ordered Value Total Frequency ADMIT 127 273 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. Model Fit Statistics Intercept Only Intercept and Covariates Criterion AIC SC 501.977 505.968 499.977 486.130 502.095 478.130 -2 Log L Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > Chisa Likelihood Ratio Score Wald The LOGISTIC Procedure 21.8469 21.5235 20.4017 <.0001 analysis of maximum likelihood estimates standard error wala chi-square parameter df estimate pr> Chisa 1 1 Intercept GRE TOPNOTCH GPA -4.6008 0.00248 0.4372 0.6676 1.0964 0.00107 0.2919 0.3253 17.6095 5.3560 2.2443 4.2123 <.0001 odds ratio estimates point estimate effect wald confidence limits gre topnotch gpa association of predicted probabilities and observed responses percent concordant discordant tied pairs somers d gamma tau-a to evaluate a graduate program data collected form the admission department like score undergraduate ranking dependent variable is binary categorical variable: admit admit. please define method use get following sas output interpret all sections output. also explain how obtain pairs. c: written by set response number levels model optimization technique logit fisher scoring observations read used profile ordered value total frequency convergence status criterion satisfied. fit statistics intercept only covariates aic sc log l testing global null hypothesis: beta="0" test chi-square df pr> Chisa Likelihood Ratio Score Wald The LOGISTIC Procedure 21.8469 21.5235 20.4017 <.0001 analysis of maximum likelihood estimates standard error wala chi-square parameter df estimate pr> Chisa 1 1 Intercept GRE TOPNOTCH GPA -4.6008 0.00248 0.4372 0.6676 1.0964 0.00107 0.2919 0.3253 17.6095 5.3560 2.2443 4.2123 <.0001 odds ratio estimates point estimate effect wald confidence limits gre topnotch gpa association of predicted probabilities and observed responses percent concordant discordant tied pairs somers d gamma tau-a>