R: Recipes for Analysis, Visualization and Machine Learning

Fitting a polynomial regression model with lm

Some predictor variables and response variables may have a non-linear relationship, and their relationship can be modeled as an nth order polynomial. In this recipe, we introduce how to deal with polynomial regression using the lm and poly functions.

Getting ready

Prepare the dataset that includes a relationship between the predictor and response variable that can be modeled as an nth order polynomial. In this recipe, we will continue to use the Quartet dataset from the car package.

How to do it...

Perform the following steps to fit the polynomial regression model with lm:

1. First, we make a scatter plot of the x and y2 variables:

   > plot(Quartet$x, Quartet$y2)
   

   Scatter plot of variables x and y2

2. You can apply ...