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  2. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    A histogram is a visual representation of the distribution of quantitative data. To construct a histogram, the first step is to "bin" (or "bucket") the range of values— divide the entire range of values into a series of intervals—and then count how many values fall into each interval.

  3. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.

  4. 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. [4]

  5. 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. [3]

  6. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    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. Another approach is to use Sturges's rule : use a bin width so that there are about 1 + log 2 ⁡ n {\displaystyle 1+\log _{2}n} non-empty bins, however this approach is not recommended ...

  7. V-optimal histograms - Wikipedia

    en.wikipedia.org/wiki/V-optimal_histograms

    A v-optimal histogram is based on the concept of minimizing a quantity which is called the weighted variance in this context. [1] This is defined as = =, where the histogram consists of J bins or buckets, n j is the number of items contained in the jth bin and where V j is the variance between the values associated with the items in the jth bin.

  8. Univariate (statistics) - Wikipedia

    en.wikipedia.org/wiki/Univariate_(statistics)

    histogram. Histograms are used to estimate distribution of the data, with the frequency of values assigned to a value range called a bin. [13] Pie charts

  9. Relative species abundance - Wikipedia

    en.wikipedia.org/wiki/Relative_species_abundance

    Relative species abundance distributions are usually graphed as frequency histograms ("Preston plots"; Figure 2) [7] or rank-abundance diagrams ("Whittaker Plots"; Figure 3). [8] Frequency histogram (Preston plot): x-axis: logarithm of abundance bins (historically log 2 as a rough approximation to the natural logarithm)