Following is the logistic regression output: Model Summary Cox & Snell R -2 Log likelihood Square Nagelkerke R Square Step 1 1139.186 .079 .112 Variable a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001. Creditability Variables in the Equation B S.E. Wald df Sig. Exp(B) Previous_Loan Step 1a Credit limit .000 .000 8.634 1 .003 1.000 Available asset -233 .074 9.899 1 .792 .002 164 Description the customer's creditability status (1: Good creditability status, 0: Bad creditability status) the customer's payment status of previous loan (0: hesitant payment of previous credits, 1: problematic running account/there are further credits running at other banks, 2: no previous credits / paid back all previous credits, 3: no problem with current credits at this bank, 4: paid back previous credits at this bank) the customer's credit limit in Euro () the customer's most valuable available assets (1: not available / no assets, 2: Car / other, 3: Savings / life insurance, 4: Ownership of house or land) the number of all the credit/loan accounts at the bank (including the current one) (1: 1, 2:2-3, 3:4-5, 4:6 and more) the customer's occupation (1: unemployed / unskilled part-time, 2: unskilled full- time, 3: skilled employee, 4: high-level executive, self-employed) Credit limit Accounts count - 193 .139 1.936 1 .824 Occupation .071 . 117 .371 1 .542 1.074 Available_asset Previous Loan .511 .077 44.516 .000 1.666 1 1 .226 1.611 Accounts_count Constant 477 .394 1.463 a. Variable(s) entered on step 1: Credit_limit, Available_asset, Accounts_count, Occupation, Previous Loan. Occupation Classification Tablea Predicted Creditability 0 Percentage Correct Observed 1 Step 1 Creditability 0 54 246 18.0 1 25 675 96.4 72.9 Overall Percentage a. The cut value is 500 Provide interpretation for Exp(B) values for variable Previous_Loan and Occupation. Following is the logistic regression output: Model Summary Cox & Snell R -2 Log likelihood Square Nagelkerke R Square Step 1 1139.186 .079 .112 Variable a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001. Creditability Variables in the Equation B S.E. Wald df Sig. Exp(B) Previous_Loan Step 1a Credit limit .000 .000 8.634 1 .003 1.000 Available asset -233 .074 9.899 1 .792 .002 164 Description the customer's creditability status (1: Good creditability status, 0: Bad creditability status) the customer's payment status of previous loan (0: hesitant payment of previous credits, 1: problematic running account/there are further credits running at other banks, 2: no previous credits / paid back all previous credits, 3: no problem with current credits at this bank, 4: paid back previous credits at this bank) the customer's credit limit in Euro () the customer's most valuable available assets (1: not available / no assets, 2: Car / other, 3: Savings / life insurance, 4: Ownership of house or land) the number of all the credit/loan accounts at the bank (including the current one) (1: 1, 2:2-3, 3:4-5, 4:6 and more) the customer's occupation (1: unemployed / unskilled part-time, 2: unskilled full- time, 3: skilled employee, 4: high-level executive, self-employed) Credit limit Accounts count - 193 .139 1.936 1 .824 Occupation .071 . 117 .371 1 .542 1.074 Available_asset Previous Loan .511 .077 44.516 .000 1.666 1 1 .226 1.611 Accounts_count Constant 477 .394 1.463 a. Variable(s) entered on step 1: Credit_limit, Available_asset, Accounts_count, Occupation, Previous Loan. Occupation Classification Tablea Predicted Creditability 0 Percentage Correct Observed 1 Step 1 Creditability 0 54 246 18.0 1 25 675 96.4 72.9 Overall Percentage a. The cut value is 500 Provide interpretation for Exp(B) values for variable Previous_Loan and Occupation
