Date were collected on y = price of car (in dollars) and x = age of car (in year) for each car in a sample of 50 used Toyota Camrys. A scatterplot showed a negative linear relationship between x and y. The least squares regression line was fit and the r2 value was computed. If x2 = 0.25, which of the following is correct statement?
(A) The correlation coefficient is positive, r - 0.5.
(B) If the least-squares line is used to predict car price based on number of miles driven, predictions should be within $0.25 of the true price.
(C) There is a strong linear relationship between car price and number of miles driven.
(D) Approximately 25% of the variability in car price can be explained by the relationship between car price and number of miles the car has been driven.