# Logistic regression with categorical data

I'm trying to apply logistic regression to the data with binary predictor. But some of my variables are numerical and some are categorical. If I just do this in R I get the model where for every categorical variable I have coefficients and p-values for for variable's possible values except for the first.

How can I interpret such model? And what is the best way of finding best model for such problem?

For factor variables, R chooses reference groups by default as the first level of that category, which does depend on the order of the levels. (When importing factors, R does this alphabetically, which is why female and non-smoker are the reference categories above. But sometimes the levels may have been applied in a different way, so it's important to check.) See relevel if you want to see how change reference categories.