In this exercise, you will investigate the relationship between a workers age an
ID: 1137458 • Letter: I
Question
In this exercise, you will investigate the relationship between a workers age and eamings. (Generally, older workers have more job experience, leading to higher productivity and eamings.) The following table contains data for full-time, full-years workers, age 25-34, with a high school diploma or B.A./B.S. as their highest degree. Download the data from the table by clicking the download table icon- A detailed description of the variables used in the dataset is available here Use a statistical package of your choice to answer the following questions Suppose you are interested in estimating the following model Ahe-po + |Age + u Run a regression of average hourly earnings (AHE) on age (Age). What is the estimated intercept po? The estimated intercept Ao is (Round your response to four decimal places) What is the estimated slope ? The estimated slope 1 is Round your response to four decimal places)Explanation / Answer
Solution: Using command lm(Ahe~Age) in R - software we get estimated intercept and coefficient corresponding to age.
1) Estimated intercept [small eta] o^ =1.0193
2) Estimated slop [small eta] 1^ =0.5464
3) B) Estimated intercept [small eta] o^ =1.0193 is not meaningful because in this case it represents worker get on an average $1.0193 dollar per hour when workers age is 0 .
4) B) Interpretation of Estimated slop [small eta] 1^ is - if workers age increases by one year ,earning increase on an average by $0.5464 dollars per hour.
5) Fitted / estimated regression model is
Ahe=1.0193 + 0.5464 * Age -----(a)
Bobs age is =29 years
predicted Bobs earning using estimated regression (a) is
Ahe=1.0193 + 0.5464 * 29=16.8649
Thus,Bobs predicted earnings are $16.8649 dollars per hour.
(6)
Alexis age is =25 years
predicted Alexis earning using estimated regression (a) is
Ahe=1.0193 + 0.5464 * 25=14.6793
Thus,Alexis predicted earnings are $16.8649 dollars per hour.
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