# Percentile vs quantile vs quartile

What is the difference between the three terms below?

• percentile
• quantile
• quartile
• A deeper question is whether quantiles etc. are intervals or points. Jun 13, 2015 at 14:20
• The quantiles are defined as points. There is often ambiguity as between intervals and points for quartiles etc.; it does not bite very hard in practice, as context usually makes clear what is intended. I prefer the first quarter (rather than quartile), for the lowest 25%, etc. although it's too much to hope that the distinction will be universally self-evident without explanation. Jun 13, 2015 at 17:22
• My answer at stats.stackexchange.com/questions/235330/… has a fuller list of *ile terms, including dates of first use. Naturally additions and earlier sightings (citings!) are welcome. Jan 16, 2019 at 16:43
• Quartile relates to quarters, i.e. out of 4. Pencentile relates to percentages, i.e. out of 100. Quantile ... is just there to confuse you (it relates to quantity). Nov 15, 2020 at 6:19

0 quartile = 0 quantile = 0 percentile

1 quartile = 0.25 quantile = 25 percentile

2 quartile = .5 quantile = 50 percentile (median)

3 quartile = .75 quantile = 75 percentile

4 quartile = 1 quantile = 100 percentile

• In case anyone else was confused looking at this: this is not saying that a quantile varies between 0 and 1, and percentile between 0 and 100, it's saying that these are the domains of the quantile(x) and percentile(x) functions, which return an observed value, the range of which is completely dependent on your specific problem (e.g. if you are measuring rainfall it's probably between 0 and 10). Apr 18, 2019 at 22:01
• Comparing this answer to one by I Like to Code below, quantile in this answer refers to a quantile function, while another usage of quantile relates to the division of [0, 1] range of probabilities into equal chunks. n-quantile means division into n chunks Jan 22 at 19:33
• Percentiles go from $0$ to $100$.

• Quartiles go from $1$ to $4$ (or $0$ to $4$).

• Quantiles can go from anything to anything.

• Percentiles and quartiles are examples of quantiles.

• If you regard the maximum as the 4th quartile then I'd suggest counting must start with regarding the minimum as the 0th quartile. Jun 13, 2015 at 11:52
• Can percentiles also be scaled to be between 0 and 1? Ex: does it make sense to say percentile(array, 0.5) (the median)? Jun 23, 2015 at 0:50
• The "percent" part of "percentile" comes from "cent" for 100. If you scale between 0 and 1 you have proportion. Of course, they are equivalent. Jun 23, 2015 at 11:12
• You can make 1000-tiles or 10,000 tiles or whatever you like. Apr 22, 2016 at 11:09
• @JosephGarvin the point Peter Flom is trying to make here is that quantiles are technically infinitely divisible whereas quartiles are not. E.g. you can have a 11.5625th quantile but only a 1st or 2nd quartile. May 5, 2020 at 21:12

In order to define these terms rigorously, it is helpful to first define the quantile function which is also known as the inverse cumulative distribution function. Recall that for a random variable $X$, the cumulative distribution function $F_X$ is defined by the equation $$F_X(x) := \Pr(X \le x).$$ The quantile function is defined by the equation $$Q(p)\,=\,\inf\left\{ x\in \mathbb{R} : p \le F(x) \right\}.$$

Now that we have got these definitions out of the way, we can define the terms:

• percentile: a measure used in statistics indicating the value below which a given percentage of observations in a group of observations fall.

Example: the 20th percentile of $X$ is the value $Q_X(0.20)$

• quantile: values taken from regular intervals of the quantile function of a random variable. For instance, for some integer $k \geq 2$, the $k$-quartiles are defined as the values i.e. $Q_X(j/k)$ for $j = 1, 2, \ldots, k - 1$.

Example: the 5-quantiles of $X$ are the values $Q_X(0.2), Q_X(0.4), Q_X(0.6), Q_X(0.8)$

• quartile: a special case of quantile, in particular the 4-quantiles. The quartiles of $X$ are the values $Q_X(0.25), Q_X(0.5), Q_X(0.75)$

It may be helpful for you to work out an example of what these definitions mean when say $X \sim U[0,100]$, i.e. $X$ is uniformly distributed from 0 to 100.

References from Wikipedia:

• Useful, but a very slight awkwardness in the middle. There is no implication in the definition that any discrete set of quantiles you focus on must be selected as regularly spaced in probability. For example, looking at something like 1, 5, 10, 25(25)75, 90, 95, 99 % points is a common part of variable summary. Jun 14, 2015 at 13:33
• @NickCox My definition for quantile was to use the definition from Wikipedia en.wikipedia.org/wiki/Quantile "Quantiles are values taken at regular intervals from the inverse of the cumulative distribution function (CDF) of a random variable." Jun 15, 2015 at 14:14
• Thanks for the reference, but I contend that using regular intervals is not part of any definition. Quantiles would not cease to be quantiles if you chose (say) 50, 75, 90, 95, 99% points. Jun 15, 2015 at 14:49
• I use Wikipedia every day fondly and distrust it mightily on anything like this. Jun 15, 2015 at 18:26
• If a specify an arbitrary value p in the interval [0 1] in the definition of Q(p) above and want to find the corresponding x, would x be called the p-quantile? Aug 31, 2021 at 18:13

From wiki page: https://en.wikipedia.org/wiki/Quantile

Some q-quantiles have special names:

The only 2-quantile is called the median
The 3-quantiles are called tertiles or terciles → T
The 4-quantiles are called quartiles → Q
The 5-quantiles are called quintiles → QU
The 6-quantiles are called sextiles → S
The 8-quantiles are called octiles  → O   (as added by @NickCox - now on wiki page also)
The 10-quantiles are called deciles → D
The 12-quantiles are called duodeciles → Dd
The 20-quantiles are called vigintiles → V
The 100-quantiles are called percentiles → P
The 1000-quantiles are called permilles → Pr


The difference between quantile, quartile and percentile becomes obvious.

• I've seen also reference to octiles (8). This list is the best argument for the single term quantiles that can be imagined. Jun 13, 2015 at 16:50
– rnso
Jun 13, 2015 at 17:06
• Thanks for the edit. I don't think these symbols are anything like standard or even well-chosen; the collective result is just alphabet soup even though it is unlikely that many would be used together. In particular, using $P$ or $Pr$ for anything but a probability is a terrible idea. Who wants to have to remember which way round $Q$ and $Qu$ are? Jun 13, 2015 at 17:17
• I don't participate in writing Wikipedia. Anyone so minded is welcome to add "octile" there. Jun 13, 2015 at 17:18

Percentile : The percent of population which lies below that value

Quantile : The cut points dividing the range of probability distribution into continuous intervals with equal probability
There are q-1 of q quantiles one of each k satisfying 0 < k < q

Quartile : Quartile is a special case of quantile, quartiles cut the data set into four equal parts i.e. q=4 for quantiles so we have First quartile Q1, second quartile Q2(Median) and third quartile Q3

• Your definitions conflict with each other and with standard ones, such as en.wikipedia.org/wiki/Percentile, which make the percentile a particular value of the population rather than a "percent of population."
– whuber
Oct 21, 2018 at 20:28
• Percentile is basically the percentage of population lies below that value for example 200 marks in CAT exam is 90 percentile that means 90 percent candidates have marks less than 200 Oct 22, 2018 at 13:13
• These definitions really don't add anything helpful to other answers. The definitions of percentile is backward, as @whuber flagged. As flagged elsewhere in the thread the definition of quantile doesn't depend on using equal intervals at all. Aug 22, 2020 at 15:29