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Re: st: Interpreting summarize, detail


From   Syed Basher <[email protected]>
To   [email protected]
Subject   Re: st: Interpreting summarize, detail
Date   Sat, 5 Feb 2011 23:02:42 -0800 (PST)

Thank you Phil, and really sorry for not following Stata FAQ 2.2. Will keep this 
in mind for future posting.

Syed Basher


----- Original Message ----
From: Phil Clayton <[email protected]>
To: [email protected]
Sent: Sun, February 6, 2011 9:19:20 AM
Subject: Re: st: Interpreting summarize, detail

You need to read it in columns, not rows. There are 3 columns of results - 
percentiles, smallest and largest 4 values, and other stats.

So the smallest 4 values for mpg are 12, 12, 14 and 14; the largest 4 values for 
mpg are 34, 35, 35 and 41. These are completely separate from the percentiles 
which are in the first column of results.

Please also see the Statalist FAQ section 2.2 "please do not start a new thread 
by replying to a previous posting"

Phil

On 06/02/2011, at 5:09 PM, Syed Basher wrote:

> Hello all,
> 
> I am having some difficulty in interpreting the basic summary statistics. 
> Consider the following:
> 
> . sysuse auto
> (1978 Automobile Data)
> 
> . summarize mpg, detail
> 
>                      Mileage (mpg)
> -------------------------------------------------------------
>    Percentiles      Smallest
> 1%            12            12
> 5%            14            12
> 10%          14            14      Obs                      74
> 25%          18            14      Sum of Wgt.          74
> 
> 50%          20                          Mean            21.2973
>                            Largest      Std. Dev.      5.785503
> 75%          25            34
> 90%          29            35      Variance      33.47205
> 95%          34            35      Skewness    .9487176
> 99%          41            41      Kurtosis      3.975005
> 
> In the above output, the largest value in 75% is 34, while the starting value 
>of 
>
> 90% is 29. The same is with the 95%. Why this is so? Shouldn't the percentile 
> value be monotonically increasing? I am interested in this because in one of my 
>
> own data, I have obtained the following output:
> 
>                          uprice
> -------------------------------------------------------------
>    Percentiles              Smallest
> 1%    .0022779        .0001697
> 5%      .01875          .0002087
> 10%    .0581161      .0010804      Obs                626
> 25%    .3826962      .0012382      Sum of Wgt.    626
> 
> 50%    1.667209                                Mean          79.44026
>                                  Largest            Std. Dev.      432.1083
> 75%    9.730152      2658.562
> 90%    77.09222      3077.629      Variance      186717.6
> 95%    363.5599      5423.877      Skewness      11.04796
> 99%      1490.65      7004.734      Kurtosis      151.0011
> 
> where as you can see I have a similar problem (largest value in 75% is much 
> higher than the starting value in 90% and so on). I am guessing that this is 
>due 
>
> to the 3rd (skewness) and 4th (kurtosis) moments of the distribution. But I do 

> not have a convincing interpretation/explanation. Your help will be much 
> appreciated.
> 
> Regards,
> 
> Syed Basher
> Qatar National Food Security Programme
> 
> 
> 
> 
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