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The term "histogram" was first introduced by Karl Pearson, the founder of mathematical statistics, in lectures delivered in 1892 at University College London.Pearson's term is sometimes incorrectly said to combine the Greek root γραμμα (gramma) = "figure" or "drawing" with the root ἱστορία (historia) = "inquiry" or "history".
Stemplot : A stemplot (or stem-and-leaf plot), in statistics, is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution. They evolved from Arthur Bowley's work in the early 1900s, and are useful tools in exploratory data analysis.
For a set of empirical measurements sampled from some probability distribution, the Freedman–Diaconis rule is designed approximately minimize the integral of the squared difference between the histogram (i.e., relative frequency density) and the density of the theoretical probability distribution.
Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots , histograms , probability plots , spaghetti plots , residual plots, box plots , block plots and biplots .
A histogram is a representation of tabulated frequencies, shown as adjacent rectangles or squares (in some of situations), erected over discrete intervals (bins), with an area proportional to the frequency of the observations in the interval. The height of a rectangle is also equal to the frequency density of the interval, i.e., the frequency ...
Considerations of the shape of a distribution arise in statistical data analysis, where simple quantitative descriptive statistics and plotting techniques such as histograms can lead on to the selection of a particular family of distributions for modelling purposes. The normal distribution, often called the "bell curve" Exponential distribution
Histogram of a sample from a right-skewed distribution – it looks unimodal and skewed right. This is a sample of size 50 from a uniform distribution, plotted as both a histogram, and a normal probability plot.
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.