# Predict the selling price of a used car, in thousands of dollars.

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Cars.com would like to use simple regression to predict the selling price of a used car, in thousands of dollars, based on the age of the car in years. A random sample of used cars was selected and the result of the regresion analysis is shown below.

 SUMMARY OUTPUT Regression Statistics Multiple R 0.7885 R Square 0.6217 Adjusted R Square 0.5461 Standard Error 1.4528 Observations 7 ANOVA df SS MS F Significance F Regression 1 17.35 17.35 8.22 0.0351 Residual 5 10.55 2.11 Total 6 27.9 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 11.69 1.24 9.424 0.0002 8.5 14.88 Sales -0.507 0.177 -2.867 0.0351 -0.962 -0.0524

### Which one of the following statements is true using alpha  = 0.05

a. Because the p-value for the slope is 0.0002, we can reject the null hypothesis and conclude that there is a relationship between the age and selling price of a used car.
b. Because the p-value for the slope is 0.0002, we fail to reject the null hypothesis and conclude that there is a relationship between the age and selling price of a used car.
c. Because the p-value for the slope os 0.0351, we can reject the null hypothesis and conclude that there is a relationship between age and selling price of a used car.
d. Because the p-value for the slope is 0.0351, we can reject the null hypothesis and conclude that there is no relationship between the age and selling price of a used car.