Dear all!!
I estimated the following OLS model with R 2.5.6:
Output R 2.5.6
Call:
lm(formula = UN ~ log(x) + time2, data = dati)
Residuals:
Min 1Q Median 3Q Max
-5.649 -2.753 -1.015 1.225 16.199
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.3036294 0.6871025 10.630 <2e-16 ***
log(x) -0.0028542 0.0270730 -0.105 0.916
time2 -0.0002670 0.0003823 -0.698 0.487
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4.323 on 87 degrees of freedom
Multiple R-Squared: 0.02933, Adjusted R-squared: 0.007017
F-statistic: 1.314 on 2 and 87 DF, p-value: 0.2739
is significant only the intercept
After I estimated the same model with R 2.7 and this is the new output:
Output R 2.7
regressione14<-lm(UN ~ log(x)+ time2,data=dati)
> summary(regressione14)
Call:
lm(formula = UN ~ log(x) + time2, data = dati)
Residuals:
Min 1Q Median 3Q Max
-8.825 -2.094 -0.861 2.233 12.664
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 22.724208 3.304670 6.876 8.89e-10 ***
log(x) -7.117981 1.499482 -4.747 8.05e-06 ***
time2 0.002051 0.000523 3.922 0.000175 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.853 on 87 degrees of freedom
Multiple R-Squared: 0.2289, Adjusted R-squared: 0.2112
F-statistic: 12.91 on 2 and 87 DF, p-value: 1.227e-05
Well, how you can see the two outputs are very differents, so i try to
estimated the same model with another package and i show the
output:
*Variabile*
*Coefficiente*
*Errore Std.*
*Statistica t*
*p-value*
const
22,7242
3,30467
6,8764
<0,00001
***
logx
-7,11798
1,49948
-4,7470
<0,00001
***
time2
0,00205144
0,000523012
3,9224
0,00017
***
Media della variabile dipendente = 6,47833
Scarto quadratico medio della variabile dipendente = 4,33827
Somma dei quadrati dei residui = 1291,58
Errore standard dei residui = 3,85302
R2 = 0,228922
R2 corretto = 0,211196
Statistica F (2, 87) = 12,9145 (p-value = 1,23e-005)
Log-verosimiglianza = -247,576
Criterio di informazione di Akaike = 501,152
Criterio bayesiano di Schwarz = 508,652
Criterio di Hannan-Quinn = 504,176
How you can see this package show the same output of the R 2.7
My question is where is the bug?
Kind regards
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