Question

The accompanying table shows a portion of data consisting of the selling price, the age, and the mileage for 20 used sedans.

Selling Price	Age	Miles
13,604	7	61,459
13,831	7	54,341
⋮	⋮	⋮
11,951	9	42,432

a. Determine the sample regression equation that enables us to predict the price of a sedan on the basis of its age and mileage. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) [If you are using R to obtain the output, then first enter the following command at the prompt: options(scipen=10). This will ensure that the output is not in scientific notation.]

PriceˆPrice^  = ____ + _____ Age + _____ Miles.

b. Interpret the slope coefficient of Age.

• The slope coefficient of Age is −0.03, which suggests that for every additional year of age, the predicted price of car decreases by $0.03.

• The slope coefficient of Age is −1021.82, which suggests that for every additional year of age, the predicted price of car decreases by $1021.82.

• The slope coefficient of Age is −384.22, which suggests that for every additional year of age, the predicted price of car decreases by $384.22, holding number of miles constant.

• The slope coefficient of Age is −0.03, which suggests that for every additional year of age, the predicted price of car decreases by $0.03, holding number of miles constant.

c. Use the predict() function in R or use the regression output to predict the selling price of a eight-year-old sedan with 66,000 miles. (Round answer to 2 decimal places.)

Price = ???

Excel Data File:

SellingPrice	Age	Miles
13604	7	61459
13831	7	54341
22923	1	8272
15260	1	24816
16417	4	22129
16644	6	23702
16920	1	47363
18436	3	16844
18832	7	35377
19848	6	29619
11820	10	55762
14967	3	46188
15910	7	36953
16453	2	45486
9464	10	86863
12961	5	77264
15765	7	59616
10470	10	93275
8948	8	48221
11951	9	42432

Answer 1

Here I attach the R code

q
q=read.csv(file.choose())
fit=lm(q$SellingPrice~q$Age+q$Miles)
fit

The fitted model is then becomes

Selling price = 21277.9441 - 384.22*Age - 0.0877*Miles

The slope coefficient is -384.22 which suggests that for every additional year of age, the predicted price of car decreases by $384.22, holding number of miles constant.

When Age=8 and Miles =66000

the Selling Price Becomes,

21277.9441 - (384.22 * 8) - (0.0877 * 66000) = 12415.98