Transformed model
As you saw in the previous chapter, transforming the variables can often transform a model from one where the technical conditions are violated to one where the technical conditions hold. When technical conditions hold, you are able to accurately interpret the inferential output. In the two models below, note how the standard errors and p-values change (although in both settings the p-value is significant).
Cet exercice fait partie du cours
Inference for Linear Regression in R
Instructions
- Run a linear regression on
priceversusbedfor theLAhomesdataset, then tidy the output. - Do the same on log-transformed variables:
log(price)versuslog(bed).
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Create a tidy model
# Create a tidy model using the log of both variables