The following diagram is a Logistics Regression coefficient table for the Universal Bank data. The "Y" variable is the dichotomous variable Loan Offer (success =1). The multiple R2 for this Logistics Regression is reported as 0.6544. The Regression Model Input variables Coefficient Std. Error p-value Odds Constant term 13.20165825 2.46772742 0.00000009 * Age 0.04453737 0.09096102 0.62439483 0.95643985 Experience 0.05657264 0.09005365 0.5298661 1.05820346 Income 0.0657607 0.00422134 0 1.06797111 Family 0.57155931 0.10119002 0.00000002 1.77102649 CCAvg 0.18724874 0.06153848 0.00234395 1.20592725 Mortgage 0.00175308 0.00080375 0.02917421 1.00175464 Securities Account 0.85484785 0.41863668 0.04115349 0.42534789 CD Account 3.46900773 0.44893095 0 32.10486984 Online 0.84355801 0.22832377 0.00022026 0.43017724 CreditCard 0.96406376 0.28254223 0.00064463 0.38134006 EducGrad 4.58909273 0.38708162 0 98.40509796 EducProf 4.52272701 0.38425466 0 92.08635712 For the Logistics Regression Model, the positive coefficients for dummy variables CD Account, EducGrad, and EducProf