Fitting a linear regression model with lm

The simplest model in regression is linear regression, which is best used when there is only one predictor variable, and the relationship between the response variable and the independent variable is linear. In R, we can fit a linear model to data with the lm function.

Getting ready

We need to prepare data with one predictor and response variable, and with a linear relationship between the two variables.

How to do it...

Perform the following steps to perform linear regression with lm:

1. You should install the car package and load its library:

> install.packages("car")> library(car)

2. From the package, you can load the Quartet dataset:

> data(Quartet)

3. You can use the str function to display the structure of the Quartet dataset:

        > str(Quartet)
        Output:
        'data.frame':   11 obs. of  6 variables:
        $ x : int  10 8 13 9 11 14 6 4 12 7 ...
        $ y1: num  8.04 6.95 7.58 8.81 8.33 ...
        $ y2: num  9.14 8.14 8.74 8.77 9...