Laura desired to make a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following:
1) Multiple R = 0.738
2) R-square = 0.546
By using lagged values she came up with the following:
3) Multiple R = 0.755
4) R-square = 0.570
Explain the differences in using these different models. How could CoffeeTime further optimize this model?