Question

Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...

Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 6.03 3.70 1.63 0.1100
Education 1.25 0.34 3.68 0.0006
Experience 0.51 0.15 3.40 0.0014
Age −0.03 0.09 −0.33 0.7404

a-1. Interpret the point estimate for β1.

  • As Education increases by 1 year, Wage is predicted to increase by 1.25/hour.

  • As Education increases by 1 year, Wage is predicted to increase by 0.51/hour.

  • As Education increases by 1 year, Wage is predicted to increase by 1.25/hour, holding Age and Experience constant.

  • As Education increases by 1 year, Wage is predicted to increase by 0.51/hour, holding Age and Experience constant.

a-2. Interpret the point estimate for β2.

  • As Experience increases by 1 year, Wage is predicted to increase by 1.25/hour.

  • As Experience increases by 1 year, Wage is predicted to increase by 0.51/hour.

  • As Experience increases by 1 year, Wage is predicted to increase by 1.25/hour, holding Age and Education constant.

  • As Experience increases by 1 year, Wage is predicted to increase by 0.51/hour, holding Age and Education constant.

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 39-year-old worker with 5 years of higher education and 5 years of experience. (Do not round intermediate calculations. Round your answer to 2 decimal places.)

Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 6.03 3.70 1.63 0.1100
Education 1.25 0.34 3.68 0.0006
Experience 0.51 0.15 3.40 0.0014
Age −0.03 0.09 −0.33 0.7404

a-1. Interpret the point estimate for β1.

  • As Education increases by 1 year, Wage is predicted to increase by 1.25/hour.

  • As Education increases by 1 year, Wage is predicted to increase by 0.51/hour.

  • As Education increases by 1 year, Wage is predicted to increase by 1.25/hour, holding Age and Experience constant.

  • As Education increases by 1 year, Wage is predicted to increase by 0.51/hour, holding Age and Experience constant.

a-2. Interpret the point estimate for β2.

  • As Experience increases by 1 year, Wage is predicted to increase by 1.25/hour.

  • As Experience increases by 1 year, Wage is predicted to increase by 0.51/hour.

  • As Experience increases by 1 year, Wage is predicted to increase by 1.25/hour, holding Age and Education constant.

  • As Experience increases by 1 year, Wage is predicted to increase by 0.51/hour, holding Age and Education constant.

b. What is the sample regression equation? (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

y^ = _______ + ______ Education + ________ Experience + _________ Age

c. Predict the hourly wage rate for a 39-year-old worker with 5 years of higher education and 5 years of experience. (Do not round intermediate calculations. Round your answer to 2 decimal places.)

y^ = ____________

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Exercise 14-23 Algo Using data from 50 workers, a researcher estimates Wage = β0 + β1Education...
Exercise 14-23 Algo Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 6.03 3.70 1.63 0.1100 Education 1.25 0.34 3.68 0.0006 Experience 0.51 0.15 3.40...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 8.36 4.05 2.06 0.0447 Education 1.96 0.35 5.60 0.0000 Experience 0.43 0.17 2.53 0.0149 Age −0.02...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 7.56 4.35 1.74 0.0889 Education 1.53 0.38 4.03 0.0002 Experience 0.42 0.12 3.50 0.0010 Age −0.04...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 8.23 4.40 1.87 0.0678 Education 1.23 0.38 3.24 0.0022 Experience 0.53 0.18 2.94 0.0051 Age −0.08...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 7.17 4.26 1.68 0.0991 Education 1.81 0.35 5.17 0.0000 Experience 0.45 0.10 4.50 0.0000 Age −0.01...
15. Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience...
15. Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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 6.89 3.61 1.91 0.0626 Education 1.29 0.34 3.79 0.0004 Experience 0.44 0.16 2.75 0.0085 Age...
Using data from 50 workers, a researcher estimates Wage = β0 + β1 Education + β2Experience...
Using data from 50 workers, a researcher estimates Wage = β0 + β1 Education + β2Experience +β3Age + 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. Coefficients Standard Error t Stat p-Value   Intercept 7.42          4.14           1.79           0.0797           Education 1.53          0.39          ...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience +...
Using data from 50 workers, a researcher estimates Wage = β0 + β1Education + β2Experience + β3Age + 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...
Using data from 50 workers, a researcher estimates Wage = β0 + β1 Education + β2...
Using data from 50 workers, a researcher estimates Wage = β0 + β1 Education + β2 Experience +β3 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. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-value   Intercept 7.58 4.42 1.71    0.0931      Education 1.68 0.37    4.54...