11.2 DESCRIPTIVE REGRESSION MODELING
The usual multiple regression model is a parametric model, defined by the following equation:
![equation](https://static.packt-cdn.com/products/9781119526810/graphics/images/c11-disp-0001.png)
where the x's represent the predictor variables, and the β's represent the unknown model parameters, whose values are estimated using the data.1 Now, estimating model parameters using sample data represents classical statistical inference. The Data Science Methodology outlined in Chapter 1, however, employs cross‐validation rather than classical statistical inference to validate model results. Thus, in this book, we will bypass the parametric regression equation above, in favor of a descriptive approach to regression modeling, using the following regression equation:
![equation](https://static.packt-cdn.com/products/9781119526810/graphics/images/c11-disp-0002.png)
In this regression equation,