Price ($)	Promotional Exp (000$)	Quality	City: 1/Suburban: 0	Sales(K)
949	5	100	1	168
941	3.5	94	1	150
934	4.8	89	1	168
921	3.6	85	1	148
915	4.3	79	1	152
909	4.7	75	1	162
904	4.5	70	1	160
1014	2	63	0	123
1006	2.9	60	0	130
990	1.2	55	0	116
978	3	51	1	142
962	3.2	47	1	145
955	3	42	1	134
953	2.8	35	0	128
1050	0.75	30	0	117
1040	1.5	26	0	118
1038	0.7	22	0	107
1022	2.4	17	0	124
1021	0	12	0	104
1018	0.25	6	0	106
1010	1.3	60	0	120
935	4.4	91	1	153

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); Quality of service (scale of 1-100); location (categorical variable: city area: 1; suburban area: 0).

Develop a multiple linear regression equation using either Excel or Minitab and based on the relevant outputs please answer the following 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, and 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 Quality and the dependent variable Monthly Sales

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