Exercise

# Model specification and estimation

You have seen the `glm()`

command for running a logistic regression. `glm()`

stands for generalized linear model and offers a whole family of regression models.

Take the exercise dataset for this coding task. The data `defaultData`

you need for this exercise is available in your environment and ready for modeling.

Instructions

**100 XP**

- Use the
`glm()`

function in order to model the probability that a customer will default on his payment by using a logistic regression. Include every explanatory variable of the dataset and specify the data that shall be used. - Do not forget to specify the argument
`family`

. - Extract the coefficients from the model, then transform them to the odds ratios and round.