Data 3.4 on page 209 describes a sample of n = 25 Mustang cars being offered for sale on the Internet. The data are stored in MustangPrice, and we want to predict the Price of each car (in $1000s) based on the Miles it has been driven (also in 1000s).
(a) Find the slope of the regression line for predicting Price based on Miles for these data.
(b) Estimate the standard error of the slope using a bootstrap distribution and use it and the normal distribution to find a98%confidence interval for the slope of this relationship in the population of all Mustangs for sale on the Internet.

Data 3.4 on page 209

A statistics student, Gabe McBride, was interested in prices for used Mustang cars being offered for sale on an Internet site. He sampled 25 cars from the website and recorded the age (in years), mileage (in thousands of miles), and asking price (in $1000s) for each car in his sample. The data are stored in MustangPrice and the scatterplot in Figure 3.26 shows the relationship between the Miles on each car and the Price. Not surprisingly, we see a strong negative association showing the price of a used Mustang tends to be lower if it has been driven for more miles. The correlation between Price and Miles for this sample is r = −0.825.