Question $2$

Please refer to the dataset Dataset Q$2.$csv$.$

This dataset is for ABC Multistate bank with following columns:

a$.$ customer$\_$id$,$ unused variable.

b$.$ credit$\_$score, used as input.

c$.$ country, used as input.

d$.$ gender, used as input.

e$.$ age, used as input.

f$.$ tenure, used as input.

g$.$ balance, used as input.

h$.$ products$\_$number, used as input.

i$.$ credit$\_$card, used as input.

j$.$ active$\_$member, used as input.

Online Postgraduate Diploma in Management: $2022-24$

Term $4|$ End$-$Term Examination Question Paper

Business Analytics

Max Marks: $35$

No$.$ of Page$($s$)$: $3$

k$.$ estimated$\_$salary, used as input.

l$.$ churn, used as the target. $1$ if the client has left the bank during some period

or $0$ if he$/$she has not.

The Aim is to predict the Customer Churn for ABC Bank.

a$.$ Estimate a Logistic Equation with the above Variables. Ensure you have an equation

that makes sense and has the $$right$$ signs for the explanatory variables and are

statistically significant $($with reasonable significance level $10\%$ atleast if not lower$).$

Before estimating the equation take time to do $$appropriate$$ flooring and capping of

the variables so that you can develop a meaningful equation.

b$.$ Compute the average churn rate for a Male Customers in Germany above $40$ years of

age?

c$.$ How will I use this data to come up with a $$rest of Europe Model $?$