The table below shows the relationship between forecasted Truckload (TL) rates (dependent variable or Y) and driver wages, equipment type and distance (the independent of X variables). Please use the information in this table to answer the following questions.

FORECAST ANALYSIS SUMMARY OUTPUT
Regression Statistics
Multiple R	0.45068
R Square	0.70311
Adjusted R Square	0.51457
Standard Error	63.83479
Observations	31
ANOVA
	df	SS	MS	F	Significance F
Regression	3	28042.40	9347.4	2.293	0.004511
Residual	27	110021.78	4074.8
Total	30	138064.19
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	60.06461313	94.40689	0.636	0.5299	-133.64232	253.77155
Driver Wages	8.321382943	3.86845	2.151	0.0405	0.38399	16.25878
Equipment Type	4.44668666	9.30575	0.477	0.6366	-14.64713	23.5405
Distance (Miles)	0.584391391	0.36973	1.580	0.0956	-0.17423	1.34302

a. What is the regression line? (3 points)

b. Is your model a significant model? How do you know? (2 points)

c. How much variation in TL rates are explained by driver wages, equipment type and distance? What is the technical name called for this variation? (2 points)

d. Which of the independent variables are significant predictors of Truckload rates (TL) at alpha = 95%? (2 points)

e. d. Which of the independent variables are significant predictors of Truckload rates (TL) at alpha = 90%? (2 points)

f. Interpret the coefficients of your significant independent variables at alpha= 95%. (2points)

g. The following are the VIF scores of the independent variables. Driver wages = 3.265; Equipment Types = 11.354; Distance (Miles) = 18.653 What do you conclude? What is your solution? (2 points).