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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.