A market analyst is interested in estimating the relationship between the miles per gallon of fuel for motorcycles (Mileage, measured in mpg) and the age of that vehicle (Age, measured in years). She collects information on 400 motorcycles across the automobile industry and estimates the following regression equation: Mileage=48.12 -2.01Age-0.04Age2, R2=0.541. (1.23) (1.25) (1.98) The standard errors are given i parentheses. She wants to find the effect on mileage of a change in age (AAge) of motorcycles. If the age of a motorcycle increases from 1 to 2 years, the predicted change in Mileage will be -2.13 mpg. (Round your answer to two decimal places. Enter a minus sign if your answer is negative.) If the age of a motorcycle increases from 7 to 8 years, the predicted change in its mpg (AMileage) will be -2.61 mpg. (Round your answer to two decimal places. Enter a minus sign if your answer is negative.) So, when the age of a motorcycle increases from 7 to 8 years, the decrease i total mileage will be higher as compared to the change when age increases from 1 to 2 years. The predicted change in mileage when the age of a motorcycle increases from 5 to 6 years is: AMileage = (Bo + ₁ ×6+₂×6²) - (Bo+B₁ ×5+₂×5²) = (6-5)₁ + (36-25)₂ = ₁ +11/₂. If the F-statistic testing the hypothesis ₁ +11/2=0 is F= 200.18, then the 95% confidence interval for the change in the predicted value of mileage is (.). (Round your answers to two decimal places. Enter a minus sign if your answer is negative.) We reject or fail to reject a hypothesis using the criterion does the hypothesized value fall in our 95% confidence interval. Based on the calculated confidence interval, we can say that at the 5% significance level, we will the