Percentile: Difference between revisions

From Citizendium
Jump to navigation Jump to search
imported>Peter Schmitt
(blanking WP import)
imported>Peter Schmitt
(new article)
Line 1: Line 1:
{{subpages}}


'''Percentiles''' are statistical parameters which describe the distribution
of a (real) value in a population (or a sample).
Roughly speaking, the ''k''-th percentile separates the smallest ''p'' percent
of values from the largest (100-''p'') percent.
Special percentiles are the [[median]] (50th percentile),
the quartiles (25th and 75th percentile),
and the deciles (the ''k''-th decile is the (10''k'')-th percentile).
Percentiles are special cases of [[quantile]]s:
The ''k''-th percentile is the same as the (''k''/100)-quantile.
== Definition ==
The value ''x'' is  ''k''-th percentile if
:    <math> P(\omega\le x) \ge {k\over100}    \textrm{\ \ and \ \ }
            P(\omega\ge x) \le 1-{k\over100}  </math>
== Special cases ==
For a continuous distribution (like the [[normal distribution]]) the
''k''-th percentile ''x'' is uniquely determined by
:    <math> P(\omega\le x) = {k\over100}    \textrm{\ \ and \ \ }
            P(\omega\ge x) = 1-{k\over100}  </math>
In the general case (e.g., for discrete distributions, or for finite samples)
it may happen that the separating value has positive probability:
:    <math> P(\omega = x) > 0 \Rightarrow
            P(\omega\le x) > {k\over100}    \textrm{\ \ and \ \ }
            P(\omega\ge x) > 1-{k\over100}  </math>
or that there are two distinct values for which equality holds
<math> x_1 < x_2 </math> such that
:    <math> P(\omega\le x_1) = {k\over100}    \textrm{\ \ and \ \ }
            P(\omega\ge x_2) = 1-{k\over100}  </math>
Then every value in the (closed) intervall between the smallest and the largest such value
<math> \left [ \min \{ x \mid P(\omega\le x) = {k\over100} \},
              \max \[ x \mid P(\omega\ge x) = 1-{k\over100} \} \right]</math>
is a ''k''-th percentiles.
== Example ==
The following examples illustrates this:
Take a sample of 101 values, ordered according to their size:
:  <math> x_1 \le x_2 \le \dots \le x_{100} \le x_{101} </math>
Then the unique ''k''-th percentile is <math>x_{k+1}</math>.
If there are only 100 values
:  <math> x_1 \le x_2 \le \dots \le x_{99} \le x_{100} </math>
then any value between <math>x_k</math> and <math>x_{k+1}</math> is a ''k''-th percentile.

Revision as of 09:30, 23 November 2009

This article is developing and not approved.
Main Article
Discussion
Related Articles  [?]
Bibliography  [?]
External Links  [?]
Citable Version  [?]
 
This editable Main Article is under development and subject to a disclaimer.

Percentiles are statistical parameters which describe the distribution of a (real) value in a population (or a sample). Roughly speaking, the k-th percentile separates the smallest p percent of values from the largest (100-p) percent.

Special percentiles are the median (50th percentile), the quartiles (25th and 75th percentile), and the deciles (the k-th decile is the (10k)-th percentile). Percentiles are special cases of quantiles: The k-th percentile is the same as the (k/100)-quantile.

Definition

The value x is k-th percentile if

Special cases

For a continuous distribution (like the normal distribution) the k-th percentile x is uniquely determined by

In the general case (e.g., for discrete distributions, or for finite samples) it may happen that the separating value has positive probability:

or that there are two distinct values for which equality holds such that

Then every value in the (closed) intervall between the smallest and the largest such value Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \left [ \min \{ x \mid P(\omega\le x) = {k\over100} \}, \max \[ x \mid P(\omega\ge x) = 1-{k\over100} \} \right]} is a k-th percentiles.

Example

The following examples illustrates this:

Take a sample of 101 values, ordered according to their size:

Then the unique k-th percentile is .

If there are only 100 values

then any value between and is a k-th percentile.