Sturges' Rule
A classical heuristic that estimates the number of classes for a histogram or grouped frequency table from the sample size.
Sturges' Rule estimates the number of classes for n observations as
k = 1 + log2(n)
≈ 1 + 3.322 log10(n)It is a starting heuristic rather than a distribution-aware optimum. Outliers, skew, multimodality, and large sample sizes can make a different binning rule more appropriate.
The rule is used in Frequency Table Generation; its broader context is covered by Frequency Table and Probability and Statistics.