Car manufacturers produced a variety of classic cars that continue to increase in value. Suppose the following data is based upon the Martin Rating System for Collectible Cars, and shows the rarity rating (1-20) and the high price ($1,000) for 15 classic cars.

Model	Rating	Price ($1,000)
A	15	52.5
B	18	350.0
C	19	4,000.0
D	16	325.0
E	14	37.0
F	17	425.0
G	17	140.0
H	16	250.0
I	19	2,675.0
J	18	1,600.0
K	16	125.0
L	13	70.0
M	19	1,300.0
N	17	425.0
O	18	1,000.0

(a)Develop a scatter diagram of the data using the rarity rating as the independent variable and price as the independent variable.

Does a simple linear regression model appear to be appropriate?

No, there appears to be a curvilinear relationship between the two variables.

Yes, there appears to be a linear relationship between the two variables.

No, there doesn't appear to be a relationship between the two variables.

(b)Develop an estimated multiple regression equation withx= rarity ratingand x² as the two independent variables. (Roundb₀andb₁to the nearest integer andb₂to one decimal place.)

=

(c)Consider the nonlinear relationship shown by equation (16.7):

E(y) =₀₁^x

Use logarithms to develop an estimated regression equation for this model. (Roundb₀to three decimal places andb₁to four decimal places.)

log() =

(d)Do you prefer the estimated regression equation developed in part (b) or part (c)? Explain.

The model in part (b) is preferred becauser²is lower and thep-value is lower.

The model in part (c) is preferred becauser²is higher and thep-value is lower.

The model in part (b) is preferred becauser²is higher and thep-value is lower.

The model in part (c) is preferred becauser²is lower and thep-value is lower.