Exercise

# Predicting with logistic models

The **logistic regression model** computes the probabilities that the given observation belongs to one of the classes.

The logistic model with two explanatory variables has the following form:

$$\frac{1}{1+e^{-(\beta_{0} + \beta_{1} \cdot x_{1} + \beta_{2} \cdot x_{2})}}$$

The R functions do the hard work for the users, but knowing the mechanics behind them will give you confidence in their correct application during the interview.

In the previous exercise, you've used the `parkinsons`

dataset and fitted the logistic regression `model`

. These two objects and the `new_person`

data frame are available in your environment.

Instructions 1/3

**undefined XP**

- Print data for the
`new_person`

. - Print the logistic regression
`model`

.