AP* Statistics Problem 6, 1997

You are planning to sell a used 1988 automobile and want to establish an asking price that is competitive with that of other cars of the same make and model that are on the market. A review of newspaper advertisements for used cars yields the following data for 12 different cars of this make and model. You want to fit a least square regression model to these data for use as a model in establishing the asking price for your car.

Production Year	1990	1991	1992	1987	1993	1991	1993	1985	1984	1982	1986	1979
Asking Price (in thousands of dollars)	6.0	7.7	8.8	3.4	9.8	8.4	8.9	1.5	1.6	1.4	2.0	1.0

The computer printouts for three different linear regression modles are shown below. Model 1 fits the asking price as a function of the production year, Model 2 fits the natural logarithm of the asking price as a function of the production year, and Model 3 fits the square root of the asking price as a function of the production year. Each printout also includes a plot of the residuals from the linear model versus the fitted values, as well as additional descriptive data produced from the least squares procedure.

1. Use Model 1 to establish an asking price for your 1988 automobile.
2. Use Model 2 to establish an asking price for your 1988 automobile.
3. Use Model 3 to establish an asking price for your 1988 automobile.
4. Describe any shortcomings you see in these three models.
5. Use some or all of the given data to find a better method for establishing an asking price for your 1988 automobile. Explain why your method is better.