You have been hired as a consultant to investigate the relationship between household monthly expenditures (Y in dollars) and three independent variables: the mortgage payment for the household (X1 in dollars), the value of the family car (X2 in dollars), and the age of the husband (X3 in years). The following multiple regression output was generated as part of your analysis.

Multiple R	0.9347
R Square	0.8737
Adjusted R Square	0.8315
ANOVA
	df	SS	MS	F	Significance F
Regression	3	4661472	1553823.9	20.7493	2.218E-04
Residual	9	674112.4	74901.378
	Coefficients	Standard Error	t Stat	P-value	Lower 95%
Intercept	106.154	908.48	-1.0442	0.3236	1106.494
Mortgage Payment (X1)	1.265	0.6329	2.3939	0.0403	2.9466
Car Value (X2)	-0.0124	0.0301	7.0901	5.73E-05	0.2819
Husband's Age (X3)	38.542	26.3014	1.8829	0.0924	109.06

i.) Write out the estimated regression equation that can be used to predict household monthly expenditures.

ii.) Conduct a test, at the 5% level of significance, to ascertain if the true value of all the regression coefficients could be zero. State the null and alternate hypotheses then provide a conclusion based on the regression output above.

iii.) Interpret each of the estimated regression coefficients of the regression model.

iv.) Using the estimated regression equation from part (i), estimate the monthly expenditures for a household with mortgage payment pf $50,000, car value of $500,000 and husband whose age is 35.

v.) State and interpret the adjusted R Square.