ABX Delivery provides the service across all the states in Australia. Marketing manager of this company wants to identify key factors that affect the time to unload a truck. A random sample of 50 deliveries was observed following data were reported.

Time to unload a truck (in minutes),

total number of cartons and

the total weight (in hundreds of Kilograms).

Following tables shows the regression output of the sample data set.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.836420803
R Square	0.699599759
Adjusted R Square	0.68681677
Standard Error	8.823384264
Observations	50

ANOVA
	df	SS	MS	F	Significance F
Regression	2	8521.530836	4260.765	54.72897	0.000000
Residual	47	3659.049164	77.85211
Total	49	12180.58

	Coefficients	Standard Error	t Stat	P-value
Intercept	-13.669	7.829028389	-1.74599	0.087346
Cartons	0.5172	0.067246763	7.691119	0.000000
Weight	0.2901	0.11166803	2.597671	0.012494

1. Determine the multiple regression equation
2. Develop hypothesis and assess the independent variables significance at 5% level?
3. How well does the model fit the data?
4. Propose minimum of 2 new explanatory variables to the model and discuss the implication of OLS assumptions in regression analysis.