The management team of a large company is studying the relationship between employees monthly expenditures (y in dollars) and three factors: The mortgage payment (x₁ in dollars), the value of the company vehicles (x₂ in dollars), and the average age of the employees (x₃ in years). As part of the analysis, you generated the multiple regression output in exhibit 1.

SUMMARY OUTPUT [Exhibit 1]
Regression Statistics
Multiple R	0.9346963
R Square	0.8736572
Adjusted R Square	0.831543
Standard Error	273.68116
Observations	13
ANOVA
	Df	SS	MS	F	Significance F
Regression	3	4661472	1553823.9	20.7493	0.0002218
Residual	9	674112.4	74901.378
Total	12	5335584
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-948.63602	908.4818	-1.044199	0.323628	-3003.766	1106.494
Mortgage Payment (x1)	1.5149792	0.632857	2.3938731	0.040301	0.0833562	2.946602
Vehicle Value (x2)	0.2137534	0.030148	7.0900756	5.73E-05	0.1455532	0.281954
Age (x3)	49.541875	26.31039	1.8829779	0.092366	-9.976397	109.0601

Required:

(a) State four (4) assumptions of the multiple linear regression model. [4marks]

(b) By outlining the F-test, comment on the overall adequacy of the multiple linear regression Model (use 5% level of significance). [4marks]

(c) Write out the estimated regression equation from the output in exhibit 1. [2marks]

(d) Interpret each of the estimated regression coefficients of the regression model. [6marks]

(e) By outlining the T-test, comment on the significance of each of the explanatory variables in the estimated regression equation (Assume 5% level of significance). [6marks]

(f) State and interpret the adjusted R.

[3marks]