Step
4:
Having explored this full model we know that some
model changes need to be made. We decide to run a Backward Selection Regression
to simplify the model.
Question
15: Provide your line of code below that will run the Backward Selection
Regression.
|
Answer: |
Question
16: Write the final regression model from the Backward Selection method and
include the appropriate R2 value for the final model.
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Answer: |
Hints
In Backward Selection Regression approach, a full model is fitted with variables in which the less significant are dropped. The same method is applied to refitted models to obtain only statistically significant variables in the models.
An R-squared increment is an amount that R^2 would change when a variable is changed.
Since the model works in a backward approach, a larger R-squared value is retained
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