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.
Cet exercice fait partie du cours
Inference for Linear Regression in R
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de 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
___