Store Size Price ($) Promotional Exp (SK) Location Sales(SK) (Sq.Ft) 949 5 1 6,500 168 941 3.5 5,200 150 934 4.8 6,400 168 921 3.6 4,750 148 915 4.3 5,250 152 909 4.7 1 6,000 162 904 4.5 1 6,000 160 1014 2 0 2,350 123 1006 2.9 0 3,000 130 990 1.2 0 2,400 116 978 3 1 5,200 142 962 3.2 1 6,000 145 955 3 1 3,700 134 953 2.8 0 4,000 128 1050 0.75 0 3,200 117 1040 1.5 3,110 118 1038 0.7 0 2,500 107 1022 2.4 0 4,000 124 1021 0 0 2,000 104 1018 0.25 0 2,300 106 1010 1.3 0 2,800 120 935 4.4 1 3,200 153 1015 2.25 1 3,500 125 1006 2.9 0 3,600 130 999 1.1 0 2,000 118 978 3 1 5,000 142 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, b, b., b. b (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'. e. Perform the overall F- test and comment on the significance of the model.