Using data from 50 workers, a researcher estimates Wage = 60 + 61Education + 62Experience + 63Age + ɛ, 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. Standard Coefficients Error t Stat p-Value 4.12 Intercept Education 6.11 1.48 0.1449 1.14 0.30 3.80 0.0004 Experience Age 0.0184 0.7764 0.44 0.18 2.44 -0.02 0.07 -0.29 a-1. Interpret the point estimate for 61.

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b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal
places.)
ý =
Education +
Experience +
Age
c. Predict the hourly wage rate for a 29-year-old worker with 3 years of higher education and 4 years of experience. (Do not round
intermediate calculations. Round your answer to 2 decimal places.)
Transcribed Image Text:b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) ý = Education + Experience + Age c. Predict the hourly wage rate for a 29-year-old worker with 3 years of higher education and 4 years of experience. (Do not round intermediate calculations. Round your answer to 2 decimal places.)
Using data from 50 workers, a researcher estimates Wage = 6g + 61Education + 62Experience + 63Age + ɛ, 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.
Standard
Coefficients
Error
t Stat
p-Value
4.12
1.48
Intercept
Education
6.11
0.1449
1.14
0.30
3.80
0.0004
Experience
Age
0.44
0.18
2.44
0.0184
-0.02
0.07
-0.29
0.7764
a-1. Interpret the point estimate for 61.
O As Education increases by 1 year, Wage is predicted to increase by 1.14/hour.
O As Education increases by 1 year, Wage is predicted to increase by 0.44/hour.
O As Education increases by 1 year, Wage is predicted to increase by 1.14/hour, holding Age and Experience constant.
As Education increases by 1 year, Wage is predicted to increase by 0.44/hour, holding Age and Experience constant.
a-2. Interpret the point estimate for 62.
O As Experience increases by 1 year, Wage is predicted to increase by 1.14/hour.
As Experience increases by 1 year, Wage is predicted to increase by 0.44/hour.
O As Experience increases by 1 year, Wage is predicted to increase by 1.14/hour, holding Age and Education constant.
O As Experience increases by 1 year, Wage is predicted to increase by 0.44/hour, holding Age and Education constant.
Transcribed Image Text:Using data from 50 workers, a researcher estimates Wage = 6g + 61Education + 62Experience + 63Age + ɛ, 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. Standard Coefficients Error t Stat p-Value 4.12 1.48 Intercept Education 6.11 0.1449 1.14 0.30 3.80 0.0004 Experience Age 0.44 0.18 2.44 0.0184 -0.02 0.07 -0.29 0.7764 a-1. Interpret the point estimate for 61. O As Education increases by 1 year, Wage is predicted to increase by 1.14/hour. O As Education increases by 1 year, Wage is predicted to increase by 0.44/hour. O As Education increases by 1 year, Wage is predicted to increase by 1.14/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.44/hour, holding Age and Experience constant. a-2. Interpret the point estimate for 62. O As Experience increases by 1 year, Wage is predicted to increase by 1.14/hour. As Experience increases by 1 year, Wage is predicted to increase by 0.44/hour. O As Experience increases by 1 year, Wage is predicted to increase by 1.14/hour, holding Age and Education constant. O As Experience increases by 1 year, Wage is predicted to increase by 0.44/hour, holding Age and Education constant.
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