Logistic regression is applied increasingly to large financial databases, such as for credit scoring to model the influence of predictors on whether a consumer is creditworthy. The data archive found...

Logistic regression is applied increasingly to large financial databases, such as for credit scoring to model the influence of predictors on whether a consumer is creditworthy. The data archive found under the index atwww.stat.uni-muenchen.decontains such a data set that includes 20 covariates for 1000 observations. Build a model for creditworthiness using the predictors running account, duration of credit, payment of previous credits, intended use, gender, and marital status.