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Using data from 50 workers, a researcher estimates Wage = ẞo + B₁Education + 2Experience + ẞ3Age + 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 Intercept 6.08 4.15 1.47 p-Value 0.1497 Education 1.24 0.34 3.65 0.0007 Experience 0.48 0.18 2.67 0.0105 Age -0.04 0.09 -0.44 0.6588 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.48/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.) |ŷ= Education + Experience + Age

Using data from 50 workers, a researcher estimates Wage = ẞo + B₁Education + 2Experience + ẞ3Age + 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 Intercept 6.08 4.15 1.47 p-Value 0.1497 Education 1.24 0.34 3.65 0.0007 Experience 0.48 0.18 2.67 0.0105 Age -0.04 0.09 -0.44 0.6588 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.48/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.) |ŷ= Education + Experience + Age

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Using data from 50 workers, a researcher estimates Wage = ẞo + B₁Education + 2Experience + ẞ3Age + 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 Intercept 6.08 4.15 1.47 p-Value 0.1497 Education 1.24 0.34 3.65 0.0007 Experience 0.48 0.18 2.67 0.0105 Age -0.04 0.09 -0.44 0.6588 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.48/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.) |ŷ= Education + Experience + Age
Transcribed Image Text:Using data from 50 workers, a researcher estimates Wage = ẞo + B₁Education + 2Experience + ẞ3Age + 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 Intercept 6.08 4.15 1.47 p-Value 0.1497 Education 1.24 0.34 3.65 0.0007 Experience 0.48 0.18 2.67 0.0105 Age -0.04 0.09 -0.44 0.6588 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour. As Education increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.48/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 0.48/hour. ○ As Experience increases by 1 year, Wage is predicted to increase by 1.24/hour, holding Age and Education constant. As Experience increases by 1 year, Wage is predicted to increase by 0.48/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.) |ŷ= Education + Experience + Age
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