Commonly, we compare an empirical distribution with known theoretical distribution. The most popular and most used theoretical distribution is the normal distribution. To compare an empirical distribution with a normal distribution, we use a normal Q-Q plot. In this recipe, we will see how we can compare a distribution of a numeric variable with the theoretical normal distribution through a normal Q-Q plot.
The data for this recipe is generated using the following code:
# Set a seed value to make the data reproducible set.seed(12345) qqdata <-data.frame(disA=rnorm(n=100,mean=20,sd=3), disB=rnorm(n=100,mean=25,sd=4), disC=rnorm(n=100,mean=15,sd=1.5), age=sample((c(1,2,3,4)),size=100,replace=T), sex=sample(c("Male","Female"),size=100,replace=T), econ_status=sample(c("Poor","Middle","Rich"), size=100,replace=T))