Please consider the data presented above for the monthly sales of Ever-cool brand of refrigerators in 1,000s of dollars (Dependent Variable) and the four independent variables. Independent variables are: Price (in dollars); Promotional Expenditure (in 1,000s of dollars); Location (categorical variable: city area: 1; suburban area: 0); Store Size (Sq.Ft) Develop a multiple linear regression equation using the Excel Data Analysis tool 'Regression' and based on the relevant outputs please answer the following five questions:

A. Based on the relevant residual and normality plots, do you see any evidence of violation of assumptions (Linearity, Normality, Equal variance)? Please explain your answer. You must attach the relevant plots as part of your report.

B. State the multiple regression equation and interpret the statistical meaning of the estimated slopes, b1, b2, b3, & b4 (corresponding to the four independent variables).

C. At the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. Based on these results, indicate the independent variable(s) to include in this model. (Based on t - test results)

D. What is the 95% confidence interval estimate of the population slope between the independent variable 'Price' and the dependent variable 'Monthly Sales' (?1)

E.. Perform the overall F- test and comment on the significance of the model.

Please follow the following instructions: ? Use Excel to run the analysis. (If you do not submit original Excel Regression Analysis output along with your answers, you will not get any credit for the case study)