Using data from 50 workers, a researcher estimates Wage = β_{0} + β_{1}Education + β_{2}Experience + β_{3}Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table.
Coefficients | Standard Error |
t Stat | p-Value | |
Intercept | 6.69 | 4.23 | 1.58 | 0.1206 |
Education | 1.13 | 0.34 | 3.32 | 0.0018 |
Experience | 0.37 | 0.10 | 3.70 | 0.0006 |
Age | −0.09 | 0.06 | −1.50 | 0.1404 |
b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)
c. Predict the hourly wage rate for a 36-year-old worker with 5 years of higher education and 4 years of experience. (Do not round intermediate calculations. Round your answer to 2 decimal places.)
We are given the regression results here.
b) The sample regression equation is obtained from the coefficients column of the table as:
Putting the values from the table, we have here:
This is the required regression equation here.
c) The hourly wage here is predicted using the given set of values of independent variables as:
Therefore 10.58 is the required hourly wage for the given worker here.
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