The following computer output shows an estimated equation. Here; W: Weekly wage. MALE: Gender, takes the value of 1 if the worker is male and 0 if female. EDU: Education Level, EDU1=1 if the worker has no formal education and 0 otherwise, EDU2=1 if the worker has primary education and 0 otherwise, EDU3=1 if the worker has secondary and high school degree and 0 otherwise, EDU4=1 if the worker has bachelor, master, and/or Ph.D. degree and 0 otherwise. EXP: Experience (the number of years being employed). Dependent Variable: W Method: Least Squares Date: 01/02/21 Time: 09:15 Sample: 1 935 Included observations: 935 Variable Coefficient Std. Error t-Statistic Prob. C 508.7969 49.56471 10.26531 0.0000 MALE 486.2831 20.27897 23.97967 0.0000 EDU2 37.93184 35.58875 1.065838 0.2868 EDU3 153.9977 40.51264 3.801225 0.0002 EDU4 251.2214 40.92353 6.138799 0.0000 EXP 10.28997 2.548076 4.038331 0.0001 R-squared 0.461610 Mean dependent var 957.9455 Adjusted R-squared 0.458713 S.D. dependent var 404.3608 S.E. of regression 297.4973 Akaike info criterion 14.23508 Sum squared resid 82220789 Schwarz criterion 14.26615 Log likelihood -6648.902 Hannan-Quinn criter. 14.24693 F-statistic 159.3033 Durbin-Watson stat 0.446774 Prob(F-statistic) 0.000000 a) Write out the estimated wage model below (use 1-digit for decimal): b) Check the statistical significance of EXP, and EDU2 at 5 % level respectively (hypothesis tests) below: 6 c) Interpret the coefficient of determination below: d) Interpret the coefficients of MALE, EDU3, and EXP below:
Unitary Method
The word “unitary” comes from the word “unit”, which means a single and complete entity. In this method, we find the value of a unit product from the given number of products, and then we solve for the other number of products.
Speed, Time, and Distance
Imagine you and 3 of your friends are planning to go to the playground at 6 in the evening. Your house is one mile away from the playground and one of your friends named Jim must start at 5 pm to reach the playground by walk. The other two friends are 3 miles away.
Profit and Loss
The amount earned or lost on the sale of one or more items is referred to as the profit or loss on that item.
Units and Measurements
Measurements and comparisons are the foundation of science and engineering. We, therefore, need rules that tell us how things are measured and compared. For these measurements and comparisons, we perform certain experiments, and we will need the experiments to set up the devices.
The following computer output shows an estimated equation. Here; W: Weekly wage.
MALE: Gender, takes the value of 1 if the worker is male and 0 if female. EDU:
Education Level, EDU1=1 if the worker has no formal education and 0 otherwise,
EDU2=1 if the worker has primary education and 0 otherwise, EDU3=1 if the worker
has secondary and high school degree and 0 otherwise, EDU4=1 if the worker has
bachelor, master, and/or Ph.D. degree and 0 otherwise. EXP: Experience (the
number of years being employed).
Dependent Variable: W
Method: Least Squares
Date: 01/02/21 Time: 09:15
Sample: 1 935
Included observations: 935
Variable Coefficient Std. Error t-Statistic Prob.
C 508.7969 49.56471 10.26531 0.0000
MALE 486.2831 20.27897 23.97967 0.0000
EDU2 37.93184 35.58875 1.065838 0.2868
EDU3 153.9977 40.51264 3.801225 0.0002
EDU4 251.2214 40.92353 6.138799 0.0000
EXP 10.28997 2.548076 4.038331 0.0001
R-squared 0.461610 Mean dependent var 957.9455
Adjusted R-squared 0.458713 S.D. dependent var 404.3608
S.E. of regression 297.4973 Akaike info criterion 14.23508
Sum squared resid 82220789 Schwarz criterion 14.26615
Log likelihood -6648.902 Hannan-Quinn criter. 14.24693
F-statistic 159.3033 Durbin-Watson stat 0.446774
Prob(F-statistic) 0.000000
a) Write out the estimated wage model below (use 1-digit for decimal):
b) Check the statistical significance of EXP, and EDU2 at 5 % level respectively
(hypothesis tests) below:
6
c) Interpret the coefficient of determination below:
d) Interpret the coefficients of MALE, EDU3, and EXP below:
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