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 | 9 | 8.1 | ||||||||
2 | 7 | 6.0 | ||||||||
3 | 11 | 3.6 | ||||||||
4 | 12 | 4.0 | ||||||||
5 | 8 | 5.0 | ||||||||
6 | 7 | 10.0 | ||||||||
7 | 8 | 7.6 | ||||||||
8 | 11 | 8.0 | ||||||||
9 | 10 | 8.0 | ||||||||
10 | 12 | 6.0 | ||||||||
11 | 6 | 8.6 | ||||||||
12 | 6 | 8.0 | ||||||||
Click here for the Excel Data File
Determine the standard error of estimate. (Round your answer to 3 decimal places.)
Determine the coefficient of determination. (Round your answer to 2 decimal places.)
Interpret the coefficient of determination. (Round your answer to the nearest whole number.)
Let X: age , Y : selling price
coefficient of determination
R-sq = (SSR/SST) = ( 10.9674 / 40.8892 ) = 0.2682
R-sq = 26.82%
Interpretation: 26.82% variation in dependent variable selling price explained by independent variable age.