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A bank is interested in identifying different attributes of its customers and below is the sample data of 150 customers. In the data table for the dummy variable Gender, 0 represents Male and 1 represents Female. And for the dummy variable Personal loan, 0 represents a customer who has not taken personal loan and 1 represents a customer who has taken personal loan.
Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Use logistic regression to classify observations as Personal loan taken (or not taken) using Age, Gender, Work experience, Income (in 1000 $), and Family size as input variables and Personal loan as the output variable. Perform an exhaustive-search best subset selection with the number of best subsets equal to 2.
a. From the generated set of logistic regression models, select one that you believe is a good fit. Express the model as a mathematical equation relating the output variable to the input variables.
b. Increases in which variables increase the chance of a customer who has taken the personal loan? Increases in which variables decrease the chance of a customer who has not taken the personal loan?
c. Using the default cutoff value of 0.5 for your logistic regression model, what is the overall error rate on the test data?
Causal Factors
Elements or conditions that can directly influence the occurrence or development of a phenomenon or outcome.
Population Efficacy
The effectiveness of a treatment or intervention when applied to a broad population under 'real-world' conditions.
Interventions
Actions or processes conducted to modify an outcome or conditions in a study or therapeutic context.
Random Sample
A subset of a statistical population in which each member of the subset has an equal probability of being chosen.
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