In this exercise, you will investigate the relationship between a worker's age and earnings. (Generally, older workers have more job experience, leading to higher productivity and earnings.) The following table contains data for fulltime, fullyears workers, age 2534, with a high school diploma or B.A.IB.S. as their highest degree. Download the data from the table by clicking the download table icon CI . A detailed description of the variables used in the dataset is available here 0 . Use a statistical package of your choice to answer the following questions. Suppose you are interested in estimating the following model Ahe =o +1Age + u Run a regression of average hourly earnings (AHE) on age (Age). What is the estimated intercept 20? The estimated intercept do is - 9.9617 . (Round your response to four decimal places) What is the estimated slope 1 ? The estimated slope Z1 is 1.0034 . (Round your response to four decimal places) Is the estimated intercept o meaningful in this case'? x Yes. No. Interpret the estimated slope 21. If a worker's age increases by 1.0034 year, earnings increase, on average, by $10034 dollars per hour. If a worker's age increases by 1 year, earnings increase, on average, by 100.34%. If a worker's age increases by 1.0034 year, earnings increase, on average, by 1 dollars per hour. If a worker's age increases by 1 year, earnings increase, on average, by $1.0034 dollars per hour. Bob's is a 28-year-old worker. Predict Bob's earnings using the estimated regression. Bob's predicted earnings are $ dollars per hour. (Round your response to two decimal places) Variable Definitions Variable Definition Ahe Average hourly earnings. Age Age in years