Percentile

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

$P(\omega \leq x)\geq {k \over 100}{\textrm {\ \ and\ \ }}P(\omega \geq x)\leq 1-{k \over 100}$

Special cases

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

$P(\omega \leq x)={k \over 100}{\textrm {\ \ and\ \ }}P(\omega \geq x)=1-{k \over 100}$

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

$P(\omega =x)>0\Rightarrow P(\omega \leq x)>{k \over 100}{\textrm {\ \ and\ \ }}P(\omega \geq x)>1-{k \over 100}$

or that there are two distinct values for which equality holds $x_{1}<x_{2}$ such that

$P(\omega \leq x_{1})={k \over 100}{\textrm {\ \ and\ \ }}P(\omega \geq x_{2})=1-{k \over 100}$

Then every value in the (closed) intervall between the smallest and the largest such value

$\left[\min \left\{x{\Bigl \vert }P(\omega \leq x)={k \over 100}\right\},\max \left\{x{\Bigl \vert }P(\omega \geq x)=1-{k \over 100}\right\}\right]$

is a k-th percentiles.

Example

The following examples illustrates this:

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

$x_{1}\leq x_{2}\leq \dots \leq x_{100}\leq x_{101}$

Then the unique k-th percentile is $x_{k+1}$.

If there are only 100 values

$x_{1}\leq x_{2}\leq \dots \leq x_{99}\leq x_{100}$

then any value between $x_{k}$ and $x_{k+1}$ is a k-th percentile.