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  2. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    bins should be used. [7] 10000 samples from a normal distribution binned using different rules. The Scott rule uses 48 bins, the Terrell-Scott rule uses 28 and Sturges's rule 15. This rule is also called the oversmoothed rule [7] or the Rice rule, [8] so called because both authors worked at Rice University.

  3. Senioritis - Wikipedia

    en.wikipedia.org/wiki/Senioritis

    Senioritis is the colloquial name for the decreased motivation toward education felt by students who are nearing the end of their high school, college, graduate school careers, or the end of a school year in general. Senioritis can, however, be described for any grade, although mostly said to occur in senior-level students.

  4. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    10000 samples from a normal distribution data binned using different rules. The Freedman-Diaconis rule results in 61 bins, the Scott rule 48 and Sturges' rule 15. With the factor 2 replaced by approximately 2.59, the Freedman–Diaconis rule asymptotically matches Scott's Rule for data sampled from a normal distribution.

  5. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    Sturges's formula implicitly bases bin sizes on the range of the data, and can perform poorly if n < 30, because the number of bins will be small—less than seven—and unlikely to show trends in the data well. On the other extreme, Sturges's formula may overestimate bin width for very large datasets, resulting in oversmoothed histograms. [14]

  6. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram.Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method.

  7. 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.

  8. Packing problems - Wikipedia

    en.wikipedia.org/wiki/Packing_problems

    In a bin packing problem, people are given: A container, usually a two- or three-dimensional convex region, possibly of infinite size. Multiple containers may be given depending on the problem. A set of objects, some or all of which must be packed into one or more containers. The set may contain different objects with their sizes specified, or ...

  9. Bucket sort - Wikipedia

    en.wikipedia.org/wiki/Bucket_sort

    Bucket sort can be seen as a generalization of counting sort; in fact, if each bucket has size 1 then bucket sort degenerates to counting sort. The variable bucket size of bucket sort allows it to use O(n) memory instead of O(M) memory, where M is the number of distinct values; in exchange, it gives up counting sort's O(n + M) worst-case behavior.