# Freedman–Diaconis rule

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In statistics, the Freedman–Diaconis rule, named after David A. Freedman and Persi Diaconis, can be used to select the size of the bins to be used in a histogram.[1] The general equation for the rule is:

${\displaystyle {\text{Bin size}}=2\,{\text{IQR}}(x)n^{-1/3}\;}$

where ${\displaystyle \scriptstyle \operatorname {IQR} (x)\;}$ is the interquartile range of the data and ${\displaystyle \scriptstyle n\;}$ is the number of observations in the sample ${\displaystyle \scriptstyle x.\;}$

## Other approaches

Another approach is to use Sturges' rule: use a bin so large that there are about ${\displaystyle \scriptstyle 1+\log _{2}n}$ non-empty bins (Scott, 2009).[2] This works well for n under 200, but was found to be inaccurate for large n.Template:Cn For a discussion and an alternative approach, see Birgé and Rozenholc.[3]

## References

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