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From |
Phil Clayton <philclayton@internode.on.net> |

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. 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 > > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Interpreting summarize, detail***From:*Syed Basher <syed.basher@yahoo.com>

**References**:**st: survey bootstrap***From:*Jun Xu <mystata@hotmail.com>

**Re: st: survey bootstrap***From:*Steven Samuels <sjsamuels@gmail.com>

**st: Interpreting summarize, detail***From:*Syed Basher <syed.basher@yahoo.com>

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