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Re: st: Interpreting summarize, detail

 From Phil Clayton To statalist@hsphsun2.harvard.edu Subject Re: st: Interpreting summarize, detail Date Sun, 6 Feb 2011 17:19:20 +1100

```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.

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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```