Bo Using data from 50 workers, a researcher estimates Wage = ẞe + B₁Education + B2Experience + B3Age + 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. A portion of the regression results is shown in the following table. Intercept Education Experience Age Coefficients Standard Error t Stat p-Value 7.17 4.26 1.68 0.0991 1.81 0.35 5.17 0.0000 0.45 0.10 4.50 0.0000 -0.01 0.06 -0.17 0.8684 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant. a-2. Interpret the point estimate for $2. As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour. As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour. As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Education constant. b. What is the sample regression equation? Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. ŷ = + Education + Experience + Age c. Predict the hourly wage rate for a 22-year-old worker with 3 years of higher education and 4 years of experience. Note: Do not round intermediate calculations. Round your answer to 2 decimal places. ŷ

Practical Management Science
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ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter13: Regression And Forecasting Models
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Using data from 50 workers, a researcher estimates Wage = ẞe + B₁Education + B2Experience + B3Age + 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. A portion of the regression results is shown in the following table.
Intercept
Education
Experience
Age
Coefficients
Standard
Error
t Stat
p-Value
7.17
4.26
1.68
0.0991
1.81
0.35
5.17
0.0000
0.45
0.10
4.50
0.0000
-0.01
0.06
-0.17
0.8684
a-1. Interpret the point estimate for ẞ1.
As Education increases by 1 year, Wage is predicted to increase by 1.81/hour.
As Education increases by 1 year, Wage is predicted to increase by 0.45/hour.
As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant.
As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant.
a-2. Interpret the point estimate for $2.
As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour.
As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour.
As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Education constant.
As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Education constant.
b. What is the sample regression equation?
Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.
ŷ =
+
Education +
Experience +
Age
c. Predict the hourly wage rate for a 22-year-old worker with 3 years of higher education and 4 years of experience.
Note: Do not round intermediate calculations. Round your answer to 2 decimal places.
ŷ
Transcribed Image Text:Bo Using data from 50 workers, a researcher estimates Wage = ẞe + B₁Education + B2Experience + B3Age + 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. A portion of the regression results is shown in the following table. Intercept Education Experience Age Coefficients Standard Error t Stat p-Value 7.17 4.26 1.68 0.0991 1.81 0.35 5.17 0.0000 0.45 0.10 4.50 0.0000 -0.01 0.06 -0.17 0.8684 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant. a-2. Interpret the point estimate for $2. As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour. As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour. As Experience increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Education constant. b. What is the sample regression equation? Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. ŷ = + Education + Experience + Age c. Predict the hourly wage rate for a 22-year-old worker with 3 years of higher education and 4 years of experience. Note: Do not round intermediate calculations. Round your answer to 2 decimal places. ŷ
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