# Default: Credit Card Default Data In ISLR: Data for an Introduction to Statistical Learning with Applications in R

## Description

A simulated data set containing information on ten thousand customers. The aim here is to predict which customers will default on their credit card debt.

## Usage

 `1` ```Default ```

## Format

A data frame with 10000 observations on the following 4 variables.

`default`

A factor with levels `No` and `Yes` indicating whether the customer defaulted on their debt

`student`

A factor with levels `No` and `Yes` indicating whether the customer is a student

`balance`

The average balance that the customer has remaining on their credit card after making their monthly payment

`income`

Income of customer

Simulated data

## References

James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) An Introduction to Statistical Learning with applications in R, www.StatLearning.com, Springer-Verlag, New York

## Examples

 ```1 2``` ```summary(Default) glm(default~student+balance+income,family="binomial",data=Default) ```

### Example output

``` default    student       balance           income
No :9667   No :7056   Min.   :   0.0   Min.   :  772
Yes: 333   Yes:2944   1st Qu.: 481.7   1st Qu.:21340
Median : 823.6   Median :34553
Mean   : 835.4   Mean   :33517
3rd Qu.:1166.3   3rd Qu.:43808
Max.   :2654.3   Max.   :73554

Call:  glm(formula = default ~ student + balance + income, family = "binomial",
data = Default)

Coefficients:
(Intercept)   studentYes      balance       income
-1.087e+01   -6.468e-01    5.737e-03    3.033e-06

Degrees of Freedom: 9999 Total (i.e. Null);  9996 Residual
Null Deviance:	    2921
Residual Deviance: 1572 	AIC: 1580
```

ISLR documentation built on May 2, 2019, 10:14 a.m.