Quartiles
Quartiles[data]
gives the quantile estimates of the elements in data.
Quartiles[data,{{a,b},{c,d}}]
uses the quantile definition specified by parameters a, b, c, d.
Quartiles[dist]
gives the quantiles of the distribution dist.
Details
- is equivalent to the median. »
- is equivalent to the average of the medians of the and smallest elements in data if is odd, and the median of the smallest elements if is even.
- is defined like , but with the largest rather than smallest elements.
- For MatrixQ data, the quartile is computed for each column vector with Quartiles[{{x1,y1,…},{x2,y2,…},…}] equivalent to {Quartiles[{x1,x2,…}],Quartiles[{y1,y2,…}]}. »
- For ArrayQ data, quartiles are equivalent to ArrayReduce[Quartiles,data,1]. »
- Quartiles[data] is equivalent to Quantile[data,{1,2,3}/4,{{1/2,0},{0,1}}]. »
- Quartiles[data,{{a,b},{c,d}}] is equivalent to Quantile[data,{1,2,3}/4,{{a,b},{c,d}}].
- Common choices of parameters {{a,b},{c,d}} include:
-
{{0,0},{1,0}} inverse empirical CDF {{0,0},{0,1}} linear interpolation (California method) {{1/2,0},{0,0}} element numbered closest to p n {{1/2,0},{0,1}} linear interpolation (hydrologist method; default) {{0,1},{0,1}} mean‐based estimate (Weibull method) {{1,-1},{0,1}} mode‐based estimate {{1/3,1/3},{0,1}} median‐based estimate {{3/8,1/4},{0,1}} normal distribution estimate - The default choice of parameters is {{1/2,0},{0,1}}. »
- The data can have the following additional forms and interpretations:
-
Association the values (the keys are ignored) » SparseArray as an array, equivalent to Normal[data] » QuantityArray quantities as an array » WeightedData based on the underlying EmpiricalDistribution » EventData based on the underlying SurvivalDistribution » TimeSeries, TemporalData, … vector or array of values (the time stamps ignored) » Image,Image3D RGB channel's values or grayscale intensity value » Audio amplitude values of all channels » DateObject, TimeObject list of dates or list of times » - Quartiles[dist] gives the list corresponding to Quantile[dist]. »
- For a random process proc, the quartiles function can be computed for slice distribution at time t, SliceDistribution[proc,t], as Quartiles[SliceDistribution[proc,t]]. »
Examples
open allclose allBasic Examples (3)
Scope (22)
Basic Uses (8)
Exact input yields exact output:
Approximate input yields approximate output:
Compute results using other parametrizations:
Find the quartiles of WeightedData:
Find the quartiles of EventData:
Find the quartiles of TemporalData:
Find the quartiles of TimeSeries:
Array Data (5)
Quartiles for a matrix gives columnwise quartiles:
Quartiles for a tensor gives columnwise medians at the first level:
When the input is an Association, Quartiles works on its values:
SparseArray data can be used just like dense arrays:
Find quartiles of a QuantityArray:
Image and Audio Data (2)
Date and Time (4)
Applications (4)
Quartiles divide a distribution in four equal probability sections:
Find a moving quartile envelope for a time series:
Data smoothed by moving median:
Moving envelope of first and third quartiles:
Find the quartiles for data representing the top oil-producing fields in 2001:
Compare with the minimum and maximum values for the data:
Plot the data with quartile lines:
Compute the quartiles for the heights of children in a class:
Properties & Relations (6)
Quartiles are given by linearly interpolated Quantile values:
The default parameters for Quantile give a different result:
The second quartile of the data is the Median:
The quantile of 1/2 does not average the two middle elements for lists of even length:
InterquartileRange is the difference between the first and third quartiles:
QuartileDeviation is half the difference between the first and third quartiles:
QuartileSkewness is a skewness measure obtained from the quartiles:
BoxWhiskerChart shows the quartiles for data:
Text
Wolfram Research (2007), Quartiles, Wolfram Language function, https://reference.wolfram.com/language/ref/Quartiles.html (updated 2024).
CMS
Wolfram Language. 2007. "Quartiles." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2024. https://reference.wolfram.com/language/ref/Quartiles.html.
APA
Wolfram Language. (2007). Quartiles. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/Quartiles.html