Summary
In this chapter, we introduced classifications through logistic regression techniques. We have first described a logistic model and then we have provided some intuitions underneath the math formulation. We learned how to define a classification problem and how to apply logistic regression to solve this type of problem. We introduced the simple logistic regression model, where the dichotomous response depends on only one explanatory variable.
Then, we generalized the logistic model to the case of more than one independent variable in the multiple logistic regression. Central arguments in dealing with multiple logistic models have been the estimate of the coefficients in the model and the tests for their significance. This has followed the same lines as the univariate model. In multiple regression, the coefficients are called partial because they express the specific relationship that an independent variable has with the dependent variable net of the other independent variables considered...
