Summarizing the model
Awesome, your last model did a really good job in predicting the sales of Hoppiness. When reporting to the company, you need to quantify this achievement and give some conclusions about the importance of the marketing activities for explaining the sales of Hoppiness.
You can get what you need in a single step by simply applying the function summary() to the extended.model object. The summary() function also summarizes information on your model regarding model fit (R-squared and Adjusted R-squared) and the importance of the effects (P-values).
This exercise is part of the course
Building Response Models in R
Exercise instructions
- Obtain the R-squared measures and the P-values for the
extended.modelobject by using the functionsummary().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Extend the sales resonse model
extended.model <- ___(log(SALES) ~ PRICE + Price.lag + DISPLAY + Display.lag + COUPON + Coupon.lag + DISPLAYCOUPON + DisplayCoupon.lag, data = sales.data)
# Summarize the model