Dependent Variable: Y Method: Least Squares Date: 07/27/20 Time: 17:10 Sample: 1 669 Included observations: 669 Variable с X R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) elect one: Coefficient Std. Error 0.087172 0.233503 0.920747 0.329976 2.790343 a. 12146.65 b. 4.267 c. 0.92 d. 18.14. t-Statistic Prob. 0.373323 0.7090 0.0054 0.011538 Mean dependent var 0.010057 S.D. dependent var 4.267419 Akaike info criterion 12146.65 Schwarz criterion -1918.993 Hannan-Quinn criter. 7.786016 Durbin-Watson stat 0.005416 rom the above regression results between Y and X, what is the estimate of error variance? 0.548234 4.289040 5.742880 5.756351 5.748098 1.912093
Dependent Variable: Y Method: Least Squares Date: 07/27/20 Time: 17:10 Sample: 1 669 Included observations: 669 Variable с X R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) elect one: Coefficient Std. Error 0.087172 0.233503 0.920747 0.329976 2.790343 a. 12146.65 b. 4.267 c. 0.92 d. 18.14. t-Statistic Prob. 0.373323 0.7090 0.0054 0.011538 Mean dependent var 0.010057 S.D. dependent var 4.267419 Akaike info criterion 12146.65 Schwarz criterion -1918.993 Hannan-Quinn criter. 7.786016 Durbin-Watson stat 0.005416 rom the above regression results between Y and X, what is the estimate of error variance? 0.548234 4.289040 5.742880 5.756351 5.748098 1.912093
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
q20-
Transcribed Image Text:Dependent Variable: Y
Method: Least Squares
Date: 07/27/20 Time: 17:10
Sample: 1 669
Included observations: 669
Variable
с
X
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Std. Error t-Statistic Prob.
0.7090
0.0054
Select one:
O a. 12146.65
O b. 4.267
O c. 0.92
O d. 18.14
Coefficient
0.087172 0.233503 0.373323
0.920747 0.329976 2.790343
0.011538 Mean dependent var
0.010057 S.D. dependent var
4.267419 Akaike info criterion
12146.65 Schwarz criterion
-1918.993 Hannan-Quinn criter.
7.786016 Durbin-Watson stat
0.005416
0.548234
4.289040
5.742880
5.756351
5.748098
1.912093
From the above regression results between Y and X, what is the estimate of error variance?
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