Adjusting for non-normal errors
In this last example, it appears as though the points are not normally distributed around the regression line. Again, note that the fix in this exercise has the effect of changing both the variability as well as modifying the linearity of the relationship.
This exercise is part of the course
Inference for Linear Regression in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Run this to see how the model looks
ggplot(hypdata_nonnorm, aes(x = explanatory, y = response)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE)
# Model response vs. explanatory
model <- ___
# Extract observation-level information
modeled_observations <- ___
# See the result
modeled_observations
# Using modeled_observations, plot residuals vs. fitted values
___