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.
We need to prepare data with one predictor and response variable, and with a linear relationship between the two variables.
Perform the following steps to perform linear regression with lm
:
- You should install the
car
package and load its library:
> install.packages("car")> library(car)
- From the package, you can load the
Quartet
dataset:
> data(Quartet)
- You can use the
str
function to display the structure of theQuartet
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...