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AW: AW: AW: st: AW: Diffrence between sum and tabsum


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   AW: AW: AW: st: AW: Diffrence between sum and tabsum
Date   Tue, 15 Sep 2009 15:30:17 +0200

<> 

" 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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Ulrich Kohler
Gesendet: Dienstag, 15. September 2009 15:22
An: statalist@hsphsun2.harvard.edu
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: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Ulrich Kohler
> Gesendet: Dienstag, 15. September 2009 14:43
> An: statalist@hsphsun2.harvard.edu
> 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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