A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) and their age (shown as "AGE" in years). The estimated GRETL outcome is shown as hereunder (numbers are made up): Model 1: OLS, using observations 1-322 Dependent variable: EARN Coefficient std. error t-ratio p-value Const 12.40443 1.862341 43.854 4.06e-06 *** YRSEDUC 5.32901 0.195032 -1.032 4.62e-033 *** AGE 1.29003 1.002893 7.281 7.59e-040 *** Mean dependent var 10.27310 S.D. dependent var 4.758696 Sum squared resid 588266.3 S.E. of regression 8.584281 R-squared 0.289671 Adjusted R-squared 0.289430

ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN:9780190931919
Author:NEWNAN
Publisher:NEWNAN
Chapter1: Making Economics Decisions
Section: Chapter Questions
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Using the findings, to answer the following questions:

A-Write down the estimated regression equation, 

B-Interpret the estimated slope coefficient of the variable "AGE".

.

A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of
education (shown as "YRSEDUC", in years) and their age (shown as "AGE" in years). The estimated GRETL outcome is shown as hereunder (numbers are made
up):
Model 1: OLS, using observations 1-322
Dependent variable: EARN
Coefficient
std. error
t-ratio
p-value
Const
12.40443
1.862341
43.854
4.06e-06
***
YRSEDUC
5.32901
0.195032
-1.032
4.62e-033 ***
AGE
1.29003
1.002893
7.281
7.59e-040 ***
Mean dependent var 10.27310
S.D. dependent var 4.758696
Sum squared resid
588266.3
S.E. of regression 8.584281
R-squared
0.289671
Adjusted R-squared 0.289430
Transcribed Image Text:A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) and their age (shown as "AGE" in years). The estimated GRETL outcome is shown as hereunder (numbers are made up): Model 1: OLS, using observations 1-322 Dependent variable: EARN Coefficient std. error t-ratio p-value Const 12.40443 1.862341 43.854 4.06e-06 *** YRSEDUC 5.32901 0.195032 -1.032 4.62e-033 *** AGE 1.29003 1.002893 7.281 7.59e-040 *** Mean dependent var 10.27310 S.D. dependent var 4.758696 Sum squared resid 588266.3 S.E. of regression 8.584281 R-squared 0.289671 Adjusted R-squared 0.289430
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