Consider the following regression forecasting the price of cars using Horsepower and Cylinders.

Regression Analysis: Price versus Horsepower, Cylinders

Analysis of Variance

Source	DF	Adj SS	Adj MS	F-Value	P-Value
Regression	__	_____________	__________	_______	0.000
Error	__	_____________	__________
Total	84	20478525206

Model Summary

S	R-sq	R-sq(adj)	R-sq(pred)
_______	75.18%	74.57%	69.81%

Coefficients

Term	Coef	SE Coef	T-Value	P-Value	VIF
Constant	-13413	3889	-3.45	0.001
Horsepower	174.1	15.6	11.13	0.000	1.81
Cylinders	742	860	0.86	0.391	____

Regression Equation

Price

=

-13413 +174.1Horsepower +742Cylinders

Fits and Diagnostics for Unusual Observations

Obs	Price	Fit	Resid	Std Resid
25	37780	60414	-22634	-2.97	R
48	51000	34129	16871	2.21	R
52	73000	74165	-1165	-0.16		X
53	120540	78343	42197	5.87	R	X
68	51600	35952	15648	2.00	R

R Large residual X Unusual X

a. Is there evidence that Horsepower is an important variable for forecasting Car Price?

b. Would you want to use the above regression model for forecasting Car Price? Please explain why/not

c. What proportion of variability in Horsepower is explained by Cylinders?