Question

19. 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
13,632	6	61,524
13,750	4	54,396
⋮	⋮	⋮
11,968	8	42,398

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 −578.38, which suggests that for every additional year of age, the predicted price of car decreases by $578.38.

• The slope coefficient of Age is −0.09, which suggests that for every additional year of age, the predicted price of car decreases by $0.09.

• The slope coefficient of Age is −578.38, which suggests that for every additional year of age, the predicted price of car decreases by $578.38, holding number of miles constant.

• The slope coefficient of Age is −0.09, which suggests that for every additional year of age, the predicted price of car decreases by $0.09, holding number of miles constant.

c. Predict the selling price of a six-year-old sedan with 66,000 miles. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

Selling Price	Age	Miles
13632	6	61524
13750	4	54396
22987	1	8251
15332	7	24862
16424	3	22147
16584	5	23745
16969	6	47378
18428	4	16821
18821	3	35399
19882	4	29623
11884	6	55811
14985	5	46177
15947	6	37046
16489	2	45510
9494	6	86900
12978	4	77245
15768	9	59692
10452	10	93278
8915	8	48255
11968	8	42398

Answer 1

Answer:

giventhat

Here we are given 3 data coloumns,

We have to predict price using age an miles .

We use multiple regression here

price = b0+b1 age +b2miles

For multiple regression we cant used excel so we need minitab here ,

In minitab enter 3 coloumns and go to STAT >>>>select regression >>>> select response price and predictors age and miles .

You get this output in minitab ,

Regression Analysis: price versus age, miles

The regression equation is
price = 22197 - 578 age - 0.0877 miles

So part a) answer is ,

price = 22197 - 578 age - 0.0877 miles

b)

here slope co-efficien of age is -518 , here decrease price 518 holding miles contact .

so correct option is C

c)

Here we have to predict price using age=6 and miles =66000

plug age=6 and miles =66000 in regression equation

price = 22197 - 578 age - 0.0877 mile

= 22197 -578(6) - 0.00877 (66000)

=18,150.18