Let's answer the questions one by one using the regression output provided: --- **b. Is this a useful model? Interpret the p-value based on a one-tailed test. (2 points)** - **Answer:** Yes, this is a useful model. The p-value for the regression (seen in the "Regression" row, under "P", as well as for the "Miles" variable) is **0.0000** (rounded). This is far less than common significance levels like 0.05 or 0.01, so we reject the null hypothesis that the coefficient for "Miles" is zero. In a one-tailed test, this means there is very strong evidence that miles are significantly related to price, and the model is useful for predicting price based on miles. --- **c. What is the y-intercept of the model? (2 points)** - **Answer:** The y-intercept (constant) of the model is **41,940.6** (rounded to one decimal place, as shown under "Constant" in the coefficient table). --- **d. Can the y-intercept be *practically* interpreted in this case (yes or no)? (2 points)** - **Answer:** **No.** The y-intercept represents the predicted price when the number of miles is zero. Practically, this means the price of a car with zero miles, which rarely happens in real life (except possibly for a brand new car, but often this regression is for used cars). Therefore, while mathematically it makes sense, it may not have a practical real-world interpretation. --- **Summary of Answers:** **b.** Yes, the p-value is 0.0000, so the model is useful; there is strong evidence that miles predict price. **c.** The y-intercept is 41,940.6. **d.** No, the y-intercept cannot be practically interpreted in this case.