Logistic model and Linear regression model I am reading the book "An introduction to statistical learning with applications in R". I am reading Logistic Regression and I don't understand why when it's compared to linear regression model, the author said that "the problem with this approach: for balances close to zero we predict a negative probability of default; if we were to predict for very large balances, we would get values bigger than 1." as in the highlight. Could anyone please explain me how the probability can be smaller than 0 or larger than 1? 

Your help is really appreciated!

Thank you
You should just keep reading:


  These predictions are not sensible, since of course the true probability of default, regardless of credit card balance, must fall between 0 and 1.


A probability cannot be smaller than 0 or larger than 1. The problem is that the model might predict such a "probability".