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  2. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    Scott's rule is a method to select the number of bins in a histogram. [1] Scott's rule is widely employed in data analysis software including R , [ 2 ] Python [ 3 ] and Microsoft Excel where it is the default bin selection method.

  3. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Histogram of 10,000 samples from a Gamma(2,2) distribution. Number of bins suggested by Scott's rule is 61, Doane's rule 21, and Sturges's rule 15. Sturges's rule is not based on any sort of optimisation procedure, like the Freedman–Diaconis rule or Scott's rule. It is simply posited based on the approximation of a normal curve by a binomial ...

  4. Data binning - Wikipedia

    en.wikipedia.org/wiki/Data_binning

    Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors.The original data values which fall into a given small interval, a bin, are replaced by a value representative of that interval, often a central value (mean or median).

  5. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    where ⁡ is the interquartile range of the data and is the number of observations in the sample . In fact if the normal density is used the factor 2 in front comes out to be ∼ 2.59 {\displaystyle \sim 2.59} , [ 4 ] but 2 is the factor recommended by Freedman and Diaconis.

  6. Bin (computational geometry) - Wikipedia

    en.wikipedia.org/wiki/Bin_(computational_geometry)

    The size of a candidate's array is the number of bins it intersects. For example, in the top figure, candidate B has 6 elements arranged in a 3 row by 2 column array because it intersects 6 bins in such an arrangement. Each bin contains the head of a singly linked list. If a candidate intersects a bin, it is chained to the bin's linked list.

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  9. Balls into bins problem - Wikipedia

    en.wikipedia.org/wiki/Balls_into_bins_problem

    This is a compromise between a deterministic allocation, in which all bins are checked and the least loaded bin is selected, and a totally random allocation, in which a single bin is selected without checking other bins. This paradigm often called the "power of two random choices" has been studied in a number of settings below. [2]

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