Editing Percentile (section)

==Definitions==
There is no standard definition of percentile;<ref name="hyndman">{{cite journal |last1=Hyndman |first1=Rob J. |author-link1=Rob J. Hyndman |last2=Fan |first2=Yanan |title=Sample Quantiles in Statistical Packages |journal=American Statistician |date=November 1996 |volume=50 |issue=4 |pages=361–365 |doi=10.2307/2684934 |jstor=2684934 |publisher=American Statistical Association |url=https://www.researchgate.net/publication/222105754}}</ref><ref>{{cite web
|url=http://cnx.org/content/m10805/latest 
|title=Percentiles
|last=Lane
|first=David
|access-date=2007-09-15}}
</ref><ref name="pottel">{{cite web
|url=http://nestor.coventry.ac.uk/~nhunt/pottel.pdf
|archive-url=https://web.archive.org/web/20130604042958/http://nestor.coventry.ac.uk/~nhunt/pottel.pdf
|archive-date=2013-06-04
|title=Statistical flaws in Excel
|last=Pottel
|first=Hans
|access-date=2013-03-25}}</ref>
however, all definitions yield similar results when the number of observations is very large and the [[probability distribution]] is continuous.<ref name="schoonjans">{{cite journal |vauthors=Schoonjans F, De Bacquer D, Schmid P |title=Estimation of population percentiles | journal=Epidemiology |volume=22 |issue=5 |pages=750–751 |year=2011 |doi=10.1097/EDE.0b013e318225c1de|pmc=3171208 |pmid=21811118}}</ref> In the limit, as the sample size approaches infinity, the 100''p''<sup>th</sup> percentile (0<''p''<1) approximates the inverse of the [[cumulative distribution function]] (CDF) thus formed, evaluated at ''p'', as ''p'' approximates the CDF. This can be seen as a consequence of the [[Glivenko–Cantelli theorem]]. Some methods for calculating the percentiles are given below.