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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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