The performance package in R lets you produce regression assumptions tests and plots. In this video I use the performance package in R to produce a set of beautiful and useful plots to check the assumptions of a linear regression. I contrast this to the plots in base R and also review some of the useful regression assumption checking functions from the package.
Subscribe below to get updates on my latest videos, courses, and other useful information.
# install and load these packages
library(performance)
library(see)
# default regression plots
model <- lm(mpg ~ wt * cyl + gear, data = mtcars)
plot(model)
# plot as a 2x2 matrix
par(mfrow = c(2, 2))
plot(model)
par(mfrow = c(1, 1))
# using the nice performance plots (zoom out if you get an error about plot size)
check_model(model)
# performance package also has functions to help check assumptions
check_normality(model)
?check_normality
check_heteroskedasticity(model)
?check_heteroskedasticity