Consider the two regression models specified below, where salary measures an employee's salary, priorexp measures the employee's years of prior experience, yrrank captures the years in the current rank, and admin indicates having experience in an administrative position. Model 1: salary 81 +8₂priorexp+e Model 2: salary =B₁ + B₂priorexp+Bayrrank + Badmin + e Analyze the results of the two models below. Model 1: MC
Consider the two regression models specified below, where salary measures an employee's salary, priorexp measures the employee's years of prior experience, yrrank captures the years in the current rank, and admin indicates having experience in an administrative position. Model 1: salary 81 +8₂priorexp+e Model 2: salary =B₁ + B₂priorexp+Bayrrank + Badmin + e Analyze the results of the two models below. Model 1: MC
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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![Question 6
Consider the two regression models specified below, where salary measures an employee's salary,
priorexp measures the employee's years of prior experience, yrrank captures the years in the
current rank, and admin indicates having experience in an administrative position.
Model 1: salary = 8₁ +8₂priorexp+e
Model 2: salary = 3₁+ B₂priorexp+ Bayrrank + Badmin + e
Analyze the results of the two models below.
Model 1:
Source
Model
Residual
Total
salary
priorexp
_cons
Model 2:
Source
Model
Residual
Total
salary
priorexp
yrrank
admin
_cons
SS
2.3573e+09
1.3938e+11
1.4174e+11
SS
df
Coef. Std. Err.
4.9146e+10
9.2594e+10
376.3852 107.6373
46709.43 602.7425
2.3573e+09
1
723 192783542
724
df
Coef. Std. Err..
451.8466 91.55876
1099.184 60.41108
10342.55 2607.254
38060.14 682.3417
c. The F-statistic equals
MS
195773163
t
MS
t
Number of obs
F(1, 723)
Prob> F
R-squared
Adj R-squared
Root MSE
P>|t|
Number of obs R
F(3, 721)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
a. In the F-test, the number of restrictions J equals
[95% Conf. Interval]
725
Consider an F-test on the joint power of yrrank and admin. Fill in the blanks below.
[95% Conf. Interval]
725
b. In the F-test, the degrees of freedom nk for the unrestricted model equals
. (Keep 1 decimal place).
d. (T/F) yrrank and admin are jointly significant factors for salary.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8c36485c-0099-4862-8f3c-a0eecaf9cef9%2Fa5e22be2-06df-4843-b390-fa0172e6d07c%2Fnfwl4xl_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Question 6
Consider the two regression models specified below, where salary measures an employee's salary,
priorexp measures the employee's years of prior experience, yrrank captures the years in the
current rank, and admin indicates having experience in an administrative position.
Model 1: salary = 8₁ +8₂priorexp+e
Model 2: salary = 3₁+ B₂priorexp+ Bayrrank + Badmin + e
Analyze the results of the two models below.
Model 1:
Source
Model
Residual
Total
salary
priorexp
_cons
Model 2:
Source
Model
Residual
Total
salary
priorexp
yrrank
admin
_cons
SS
2.3573e+09
1.3938e+11
1.4174e+11
SS
df
Coef. Std. Err.
4.9146e+10
9.2594e+10
376.3852 107.6373
46709.43 602.7425
2.3573e+09
1
723 192783542
724
df
Coef. Std. Err..
451.8466 91.55876
1099.184 60.41108
10342.55 2607.254
38060.14 682.3417
c. The F-statistic equals
MS
195773163
t
MS
t
Number of obs
F(1, 723)
Prob> F
R-squared
Adj R-squared
Root MSE
P>|t|
Number of obs R
F(3, 721)
Prob > F
R-squared
Adj R-squared
Root MSE
P>|t|
=
a. In the F-test, the number of restrictions J equals
[95% Conf. Interval]
725
Consider an F-test on the joint power of yrrank and admin. Fill in the blanks below.
[95% Conf. Interval]
725
b. In the F-test, the degrees of freedom nk for the unrestricted model equals
. (Keep 1 decimal place).
d. (T/F) yrrank and admin are jointly significant factors for salary.
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