<>
" I think -tabsum- should produce the same solution
than summarize"
Maybe this effect is related both to the "close-to-zero" thing and the OS issue. As both commands are built-in, it is difficult to look under the hood. Still, I hope you get the same answer from this more straightforward example. I certainly do...
*************
sysuse auto, clear
bys for: su mpg
tab for, sum(mpg)
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected] [mailto:[email protected]] Im Auftrag von Ulrich Kohler
Gesendet: Dienstag, 15. September 2009 15:22
An: [email protected]
Betreff: Re: AW: AW: st: AW: Diffrence between sum and tabsum
I asked a colleague of mine to run the do-file. He got the same value as
you. Seemingly, you have the Windows solution, while I have the Linux
solution. I would have expected that both are the same.
Leaving that aside, I think -tabsum- should produce the same solution
than summarize -- which is zero (or something that is so close to zero
that Stata doesn't see the difference)
uli
Am Dienstag, den 15.09.2009, 14:54 +0200 schrieb Martin Weiss:
> <>
>
> For instance, the line
>
> *************
> tab dummy, sum(firstweight)
> *************
>
> returns
>
>
>
> Summary of firstweight
> dummy Mean Std. Dev. Freq.
>
> 1 13949.146 .00021143 3
>
> Total 13949.146 .00021143 3
>
>
> for me. The sd differs from yours...
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von Ulrich Kohler
> Gesendet: Dienstag, 15. September 2009 14:43
> An: [email protected]
> Betreff: Re: AW: st: AW: Diffrence between sum and tabsum
>
> Am Dienstag, den 15.09.2009, 13:45 +0200 schrieb Martin Weiss:
> > <>
> >
> > Also note http://www.stata.com/support/faqs/data/float.html
>
> Well, yes I know that. But I still don't think that this satisfactorily
> explains the values.
>
> > I get answers different from yours, both in Stata 10.1 and 11,
>
> What do you mean that you get different answers. Do you get a zero?
>
> > possibly b/c your dataset is not created by the code that you showed in
> your reply?
> > I assume this is the case as your -list- command shows the "dummy"
> > although it is -generate-d in the following line...
>
> The dataset is created as described. I just produced the output of
> -list- later and copied it to a place where I (mistakenly) thought it
> makes things clearer.
>
> Here is one more tackle on that. The first lines of the following
> do-file reproduces the behavior on more time. The second part calculates
> the standard deviation "by hand" showing that one could circumvent the
> problem described in the FAQ. The third part changes one bit in the
> hand-made solution, which makes it coming quite close to the -tabsum-
> solution.
>
> However, I have expected that -tabsum- works like the second part.
>
> ---------------------------------------------------------11.do
> clear
> set obs 3
> gen byte coreweight1968 = 18
> gen double firstweight = coreweight1968 * 60468000/78028
> gen dummy = 1
> tab dummy, sum(firstweight)
>
> gen double sum = sum(firstweight)
> gen double mean = sum[_N]/3
> gen double diff = sum((firstweight - mean)^2)
> di %17.16f sqrt(diff[_N]/2)
>
> drop sum-diff
> gen float sum = sum(firstweight)
> gen double mean = sum[_N]/3
> gen double diff = sum((firstweight - mean)^2)
> di %17.16f sqrt(diff[_N]/2)
>
> ----------------------------------------------------------------
>
> Here is the output of the do-file without any modifications.
>
> . do 11
>
> . clear
>
> . set obs 3
> obs was 0, now 3
>
> . gen byte coreweight1968 = 18
>
> . gen double firstweight = coreweight1968 * 60468000/78028
>
> . gen dummy = 1
>
> . tab dummy, sum(firstweight)
>
> | Summary of firstweight
> dummy | Mean Std. Dev. Freq.
> ------------+------------------------------------
> 1 | 13949.146 .00024815 3
> ------------+------------------------------------
> Total | 13949.146 .00024815 3
>
> .
> . gen double sum = sum(firstweight)
>
> . gen double mean = sum[_N]/3
>
> . gen double diff = sum((firstweight - mean)^2)
>
> . di %17.16f sqrt(diff[_N]/2)
> 0.0000000000022278
>
> .
> . drop sum-diff
>
> . gen float sum = sum(firstweight)
>
> . gen double mean = sum[_N]/3
>
> . gen double diff = sum((firstweight - mean)^2)
>
> . di %17.16f sqrt(diff[_N]/2)
> 0.0007678068963647
>
> .
> .
> .
> .
> .
> .
> .
> .
> .
> .
> .
> end of do-file
>
>
>
>
>
> *
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>
>
> *
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*
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*
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