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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.