# [R] question about the degrees of freedom

Ista Zahn istazahn at gmail.com
Mon May 3 16:38:53 CEST 2010

```Hi Serdal,
There is a lot of confusion here (how much is yours and how much is
mine remains to be seen). See specific comments in line.

On Mon, May 3, 2010 at 9:19 AM, serdal ozusaglam
<saint-filth at hotmail.com> wrote:
>
> Dear R users,
>
>
> I think i have a simple question which i want to explain by an example;
>
> i have several 2-digit industry codes that i want to use for conducting by-industry analysis but i think there is a problem with the degrees of freedom!
>
> for example, when i do my analysis without any 2-digit industry code, i got the following summary (i have 146574 observations in total):
>> abc<-lm(lnQ~lnC+lnM+lnL+lnE+eco+inno, data=ds)
>> summary(abc)
>
> Call:
> lm(formula = lnQ ~ lnC + lnM + lnL + lnE + eco + inno, data = ds)
>
> Residuals:
>      Min        1Q    Median        3Q       Max
> -11.01340  -0.17637  -0.02217   0.14974   7.79005
>
> Coefficients:
>             Estimate Std. Error  t value Pr(>|t|)
> (Intercept) 0.8870369  0.0050646  175.144   <2e-16 ***
> lnC         0.0658922  0.0006549  100.614   <2e-16 ***
> lnM         0.8027478  0.0006549 1225.764   <2e-16 ***
> lnL         0.0173622  0.0004025   43.138   <2e-16 ***
> lnE         0.0657710  0.0006745   97.516   <2e-16 ***
> ecoTRUE     0.0101649  0.0045892    2.215   0.0268 *
> innoTRUE    0.0945100  0.0030317   31.174   <2e-16 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Residual standard error: 0.294 on 146160 degrees of freedom
>  (407 observations deleted due to missingness)
> Multiple R-squared: 0.9705,     Adjusted R-squared: 0.9705
> F-statistic: 8.027e+05 on 6 and 146160 DF,  p-value: < 2.2e-16
>
> as we can see from the last row there are 146160 DF (407 deleted) this is ok!
>
>

Usually it is better to make a small example that demonstrates your
issue. I have no idea what these variable are which makes it harder to

>
>
> but when i want to use for example just one of the industry lets say just the 11th industry
> 1st:  i create the dummy for this industry such as;
>
>
>>ind1=(ind_2d==11)# so here the R supposed to consider just the 11th industry!!

This makes no sense to me. What are you trying to do here? What is
ind_2d? Are you trying to subset your data.frame? If so, see ?subset,
or ?"["

>> abc<-lm(lnQ~lnC+lnM+lnL+lnE+eco+inno+ind, data=ds)
>> summary(abc)
>
> Call:
> lm(formula = lnQ ~ lnC + lnM + lnL + lnE + eco + inno + ind,
>    data = ds)
>
> Residuals:
>      Min        1Q    Median        3Q       Max
> -11.03392  -0.17647  -0.02301   0.14901   7.74957
>
> Coefficients:
>              Estimate Std. Error  t value Pr(>|t|)
> (Intercept)  0.8980397  0.0050451  178.001  < 2e-16 ***
> lnC          0.0672255  0.0006523  103.065  < 2e-16 ***
> lnM          0.7990819  0.0006579 1214.596  < 2e-16 ***
> lnL          0.0171633  0.0004004   42.870  < 2e-16 ***
> lnE          0.0670030  0.0006716   99.770  < 2e-16 ***
> ecoTRUE      0.0162249  0.0045672    3.552 0.000382 ***
> innoTRUE     0.0966967  0.0030160   32.062  < 2e-16 ***
> indTRUE     -0.1251466  0.0031509  -39.717  < 2e-16 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Residual standard error: 0.2924 on 146159 degrees of freedom
>  (407 observations deleted due to missingness)
> Multiple R-squared: 0.9709,     Adjusted R-squared: 0.9709
> F-statistic: 6.957e+05 on 7 and 146159 DF,  p-value: < 2.2e-16
>
> but as we can see it again counted in all the industries! so the DF is 146159!!!
>
>
> So i just wonder, where do i made mistake, or there is no mistake at all, and i just misunderstood the DF issue?

I think the misunderstanding runs deeper than that. Try creating a
minimal example, and clearly stating a) what you are trying to
accomplish, b) what you tried, and c) what doesn't work as you expect.

Best,
Ista

>
> Any answer would be appreciated
>
>
>
>
>
>
>
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--
Ista Zahn