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  3. Inference for Linear Regression in R

Exercise

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).

Instructions

100 XP
  • Run a linear regression on price versus bed for the LAhomes dataset, then tidy the output.
  • Do the same on log-transformed variables: log(price) versus log(bed).