Question

the owner of a used car dealership is trying to determine if there is a relationship between the price of a used car and the number of miles it has been driven. the owner collects data for 25 cars of the same model with different mileage and determines each car’s price using a used car website. the analysis is given in the computer output.

predictor | coef | se coef | t-ratio | p
constant | 24157.2 | 2164.1 | 2.965 | 0.046
mileage | -0.181 | 0.024 | 5.377 | 0.000
s = 3860.7 | r - sq = 68.0% | r - sq(adj) = 69.5%

which of the following represents the value of the average residual for a car’s price?
0.024
3860.7
24157.2
2164.1

Explanation:

Step1: Identify residual measure

In linear regression output, the value labeled $S$ represents the standard error of the estimate, which is the average (standard deviation) of the residuals.

Step2: Match to given output

From the computer output, $S = 3860.7$.

Answer:

3860.7