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Analyzing regression results

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The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price (in thousands of dollars) at which the Cadet was sold used. With the aim of predicting the used selling price from the number of miles driven, we might examine the least-squares regression line y^=41.77-0.49x. This line is shown in the scatter plot in Figure 1.

1. Fill in the blanks for these data. Mileages that are greater than the mean of the mileage tend to be paired with used prices that are --------mean of used selling prices.

2. According to the regression equation, for an increase of one thousand miles in Cadet Mileage, there is a corresponding decrease of how many thousand dollars in used selling price?

3. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 26.9 thousand miles? (Round your answer to at least one decimal place).

4. What was the observed used selling price (in thousands of dollars) when the mileage was 26.9 thousand miles?

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1. Mileages that are greater than the mean of the mileage tend to be paired with used prices that are less than the mean of used selling prices. (Line is ...

Solution Summary

Solution analyzes the regression results.

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