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

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.