Laura wanted to build a multiple regression model based on advertising expenditures and Coffee Time's price index. Based on the selection of all normal values, she obtained the following:
Multiple R = 0.738
R-Square = 0.546
By using lagged values, she came up with the following:
Multiple R = 0.755
R-Square = 0.570
Explain the differences in using these different models and how can the model be improved
Here Multiple R = 0.738 R-Square = 0.546 .Which means that the correlation between the dependent variable (coffee's price) and the set of independent variables ( advertising expenditure and ...
The solution conducts a regression analysis of advertising expenditures and Coffee Time's price index which contains slope, intercept, correlation, r-square, coefficient of determination, regression coefficients. Interpretation of the results are also given.