In: Statistics and Probability
The owner of Maumee Ford-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year.
Car | Age (years) | Selling Price ($000) | ||||||||
1 | 13 | 13.1 | ||||||||
2 | 10 | 11.8 | ||||||||
3 | 15 | 5.7 | ||||||||
4 | 17 | 4.9 | ||||||||
5 | 11 | 6.8 | ||||||||
6 | 10 | 14.0 | ||||||||
7 | 11 | 11.4 | ||||||||
8 | 15 | 9.8 | ||||||||
9 | 15 | 9.8 | ||||||||
10 | 17 | 4.5 | ||||||||
11 | 8 | 13.0 | ||||||||
12 | 8 | 11.0 | ||||||||
Determine the regression equation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.)
Estimate the selling price of an 7-year-old car (in $000). (Round your answer to 3 decimal places.)
Interpret the regression equation (in dollars). (Round your answer to the nearest dollar amount.)
I input this data set in MS Excel and use the "Regression"
option under Data > Data Analysis to carry out the regression
analysis and answer the given questions. The screenshot of the data
set and output are given below. Here, x = Age (years), y = Selling
Price ($000).
(a) The equation is:
.
(b) For
= 7, estimated selling price =
= 19.020 + (-0.750 * 7) = $13.770.
(c) For each additional year, the car decreases
$750 in value.