A researcher obtains the following STATA output by regressing salary (salary. $) on years of prior experience (priorexp). Source Model 2.3573e+09 Residual 1.3938e+11 Total salary priorexp _cons 0.0166 0.0081 SS 0,6284 What is the R2 of this model? 0.9833 1.4174e+11 Coef. df 1 723 724 Std. Err. 376.3852 107.6373 46709.43 602.7425 MS 2.3573e+09 192783542 Number of obs = F(1, 723) Prob > F R-squared t Adj R-quared 195773163 Root MSE 725 P>|t| [95% Conf. Interval]

MATLAB: An Introduction with Applications
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A researcher obtains the following STATA output by regressing salary (salary, $) on years of prior
experience (priorezp).
Source
Model
Residual
Total
salary
priorexp
_cons
0.0166
0.0081
0.6284
SS
0.9833
2.3573e+09
1.3938e+11
What is the R2 of this model?
1.4174e+11
df
1
723
724
Coef. Std. Err.
376.3852 107.6373
46709.43 602.7425
MS
2.35730+09
192783542
195773163
Number of obs
F(1, 723)
Prob > F
R-squared
Adj R-quared
Root MSE
725
t P>|t| [95% Conf. Interval]
Transcribed Image Text:A researcher obtains the following STATA output by regressing salary (salary, $) on years of prior experience (priorezp). Source Model Residual Total salary priorexp _cons 0.0166 0.0081 0.6284 SS 0.9833 2.3573e+09 1.3938e+11 What is the R2 of this model? 1.4174e+11 df 1 723 724 Coef. Std. Err. 376.3852 107.6373 46709.43 602.7425 MS 2.35730+09 192783542 195773163 Number of obs F(1, 723) Prob > F R-squared Adj R-quared Root MSE 725 t P>|t| [95% Conf. Interval]
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