Dependent Variable: ZAM_RGDP Method: Least Squares Date: 04/25/10 Time: 23:52 Sa
ID: 1243863 • Letter: D
Question
Dependent Variable: ZAM_RGDP
Method: Least Squares
Date: 04/25/10 Time: 23:52
Sample (adjusted): 1962 2006
Included observations: 45 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
5659640.
1.03E+08
0.055119
0.9563
ZAM_RGDP(-1)
0.948231
0.158017
6.000807
0.0000
ZAM_RGDP(-2)
0.072440
0.162031
0.447077
0.6571
R-squared
0.950011
Mean dependent var
2.84E+09
Adjusted R-squared
0.947630
S.D. dependent var
5.50E+08
S.E. of regression
1.26E+08
Akaike info criterion
40.20446
Sum squared resid
6.66E+17
Schwarz criterion
40.32490
Log likelihood
-901.6002
Hannan-Quinn criter.
40.24936
F-statistic
399.0894
Durbin-Watson stat
1.934214
Prob(F-statistic)
0.000000
Dependent Variable: ZAM_RGDP
Method: Least Squares
Date: 04/25/10 Time: 23:52
Sample (adjusted): 1962 2006
Included observations: 45 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
5659640.
1.03E+08
0.055119
0.9563
ZAM_RGDP(-1)
0.948231
0.158017
6.000807
0.0000
ZAM_RGDP(-2)
0.072440
0.162031
0.447077
0.6571
R-squared
0.950011
Mean dependent var
2.84E+09
Adjusted R-squared
0.947630
S.D. dependent var
5.50E+08
S.E. of regression
1.26E+08
Akaike info criterion
40.20446
Sum squared resid
6.66E+17
Schwarz criterion
40.32490
Log likelihood
-901.6002
Hannan-Quinn criter.
40.24936
F-statistic
399.0894
Durbin-Watson stat
1.934214
Prob(F-statistic)
0.000000
Explanation / Answer
The Prob( F-statistic) is the first thing you should look atbecause if this value is greater than your level of significance(i.e. your that you chose, typically it's 0.05). Looking theProb( F-statistic), which is also know as a p-value, we canconclude that the model is significant at any level of . Thistells us that model is a reasonably good one and that the rest ofthe output is worth looking at, where as if the if it was notsignificant that would tell us that the model is inherently a badmodel and the rest of the output is not worth looking at. The R-squared and the adjusted R-squared are high, which impliesthat the model is a good fit, since they can be only as high as 1and as low as zero. When looking at the variables, I'm assuming that ZAM_RGDP(-1) andZAM_RGDP(-2) are the independent variables and I will proceed fromthat assumption. You want to look at the Prob., which I know as ap-value, of each variable first this will tell you whether or noreach variable is statistical significant or not. Assuming =0.05 ZAM_RGDP(-1) is significant since 0.0000 . The interpretation of the coefficient of ZAM_RGDP(-1)is that for a 1 unit increase in ZAM_RGDP(-1) will produce a0.948321 unit change in ZAM_RGDP. We generally don't look at the constant term, C, since it usuallydoesn't have an interpretation that makes any sense, but in thiscase it's not statistically significant anyhow. The number of observations is over 30 which is good. The other junk in the output doesn't really matter unless you havea very specific question about the output or are preforming a testthat requires one of this statistics near the bottom of theoutput. **One tip though, you should generally name the variables namesthat make it intuitive to what the variables actually are inthe data. For example, If my data was of housing price as thedependent and the independent variable was the square footage ofthe house that was under central heat, I would name the variableHEATED_AREA I think that makes it easier for some one to lookat the output and understand what is going on with the databetter.Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.