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A descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features from a collection of information, [1] while descriptive statistics (in the mass noun sense) is the process of using and analysing those statistics. Descriptive statistics is distinguished from inferential statistics (or ...
d-separation; D/M/1 queue; D'Agostino's K-squared test; Dagum distribution; DAP – open source software; Data analysis; Data assimilation; Data binning; Data classification (business intelligence)
The five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles: the sample minimum (smallest observation) the lower quartile or first quartile; the median (the middle value) the upper quartile or third quartile
Data profiling utilizes methods of descriptive statistics such as minimum, maximum, mean, mode, percentile, standard deviation, frequency, variation, aggregates such as count and sum, and additional metadata information obtained during data profiling such as data type, length, discrete values, uniqueness, occurrence of null values, typical string patterns, and abstract type recognition.
The Datasaurus dozen comprises thirteen data sets that have nearly identical simple descriptive statistics to two decimal places, yet have very different distributions and appear very different when graphed. [1] It was inspired by the smaller Anscombe's quartet that was created in 1973.
In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in
The field of data and information visualization is of interdisciplinary nature as it incorporates principles found in the disciplines of descriptive statistics (as early as the 18th century), [12] visual communication, graphic design, cognitive science and, more recently, interactive computer graphics and human-computer interaction. [13]
In statistics, the sample maximum and sample minimum, also called the largest observation and smallest observation, are the values of the greatest and least elements of a sample. [1] They are basic summary statistics, used in descriptive statistics such as the five-number summary and Bowley's seven-figure summary and the associated box plot.