The cases that make up this dataset are types of cars. The data include the engine size or displacement (in liters) and horsepower (HP) of 67 vehicles sold in a certain country in 2011. Use the SRM of the horsepower on the engine displacement to complete parts (a) through (c). Click the icon to view the data table. (a) A manufacturer offers 2.4 and 3.3 liter engines in a particular model car. Based on these data, how much more horsepower should one expect the larger engine to produce? Give your answer as a 95% confidence interval. to (Round to the nearest integer as needed.) (b) Do you have any qualms about presenting this interval as an appropriate 95% range? O A. Yes, because the value of r is too low. O B. No O C. Yes, because the p-value for the two-sided hypothesis , =0 is too high. O D. Yes, because there are several outliers in the data and they will have to be removed. (c) Based on the fit of this regression model, what is the expected horsepower of a car with a 3.3 liter engine? Give your answer as a 95% prediction interval. Do you think that the standard prediction interval is reasonable? Explain. What is the expected horsepower of a car with a 3.3 liter engine using a 95% prediction interval? to (Round to the nearest integer as needed.) Do you think that the standard prediction interval is reasonable? Explain. O A. Yes, because approximately the same number of data points are above and below the regression line. O B. Yes, because the residuals of the regression are approximately normally distributed. O C. No, because even though the residuals of the regression are approximately normally distributed, the regression line underpredicts the horsepower for smaller displacement engines. O D. No, because a fan-shaped pattern occurs in the data points around the regression line and the regression line overpredicts the horsepower for smaller displacement engines