Interquartile range
This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (May 2012) |
In descriptive statistics, the interquartile range (IQR), also called the midspread or middle fifty, is a measure of statistical dispersion, being equal to the difference between the upper and lower quartiles,[1][2] IQR = Q3 − Q1
Contents |
[edit] Use
Unlike (total) range, the interquartile range is a robust statistic, having a breakdown point of 25%, and is thus often preferred to the total range.
The IQR is used to build box plots, simple graphical representations of a probability distribution.
For a symmetric distribution (where the median equals the midhinge, the average of the first and third quartiles), half the IQR equals the median absolute deviation (MAD).
The median is the corresponding measure of central tendency.
[edit] Examples
[edit] Data set in a table
-
i x[i] Quartile 1 102 2 104 3 105 Q1 4 107 5 108 6 109 Q2 (median) 7 110 8 112 9 115 Q3 10 116 11 118
For the data in this table the interquartile range is IQR = 115 − 105 = 10.
[edit] Data set in a plain-text box plot
+-----+-+ o * |-------| | |---| +-----+-+ +---+---+---+---+---+---+---+---+---+---+---+---+ number line 0 1 2 3 4 5 6 7 8 9 10 11 12
For the data set in this box plot:
- lower (first) quartile Q1 = 7
- median (second quartile) Q2 = 8.5
- upper (third) quartile Q3 = 9
- interquartile range, IQR = Q3 − Q1 = 2
[edit] Interquartile range of distributions
The interquartile range of a continuous distribution can be calculated by integrating the probability density function (which yields the cumulative distribution function — any other means of calculating the CDF will also work). The lower quartile, Q1, is a number such that integral of the PDF from -∞ to Q1 equals 0.25, while the upper quartile, Q3, is such a number that the integral from -∞ to Q3 equals 0.75; in terms of the CDF, the quartiles can be defined as follows:
where CDF−1 is the quantile function.
The interquartile range and median of some common distributions are shown below
Distribution | Median | IQR |
---|---|---|
Normal | μ | 2 Φ−1(0.75) ≈ 1.349 |
Laplace | μ | 2b ln(2) |
Cauchy | μ |
[edit] Interquartile range test for normality of distribution
The IQR, mean, and standard deviation of a population P can be used in a simple test of whether or not P is normally distributed, or Gaussian. If P is normally distributed, then the standard score of the first quartile, z1, is -0.67, and the standard score of the third quartile, z3, is +0.67. Given mean = X and standard deviation = σ for P, if P is normally distributed, the first quartile
and the third quartile
If the actual values of the first or third quartiles differ substantially from the calculated values, P is not normally distributed.
[edit] See also
[edit] References
- ^ Upton, Graham; Cook, Ian (1996). Understanding Statistics. Oxford University Press. p. 55. ISBN 0-19-914391-9. http://books.google.com/books?id=vXzWG09_SzAC&pg=PA55&dq=interquartile+range#v=onepage&q=interquartile%20range&f=false.
- ^ Zwillinger, D., Kokoska, S. (2000) CRC Standard Probability and Statistics Tables and Formulae, CRC Press. ISBN 1-58488-059-7 page 18.
|