In this recipe, we will see how to make Quantile-Quantile (Q-Q) plots, which are useful for comparing two probability distributions.
Getting ready
For this recipe, we don't need to load any additional libraries. We just need to type the recipe at the R prompt or run it as a script.
How to do it...
Let's see how the distribution of mpg in the mtcars dataset compares with a normal distribution using the qnorm() function:
qqnorm(mtcars$mpg)
qqline(mtcars$mpg)
How it works...
In the example, we used the qqnorm() function to create a normal Q-Q plot of mpg values. We added a straight line with the qqline() function. The closer the dots to this line the closer the distribution to a normal one.
There's more...
Another way of making a Q-Q plot is by calling the plot() function on a model fit. For example, let's plot the following linear model fit: