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  2. Box plot - Wikipedia

    en.wikipedia.org/wiki/Box_plot

    Figure 2. Box-plot with whiskers from minimum to maximum Figure 3. Same box-plot with whiskers drawn within the 1.5 IQR value. A boxplot is a standardized way of displaying the dataset based on the five-number summary: the minimum, the maximum, the sample median, and the first and third quartiles.

  3. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    Box-and-whisker plot with four mild outliers and one extreme outlier. In this chart, outliers are defined as mild above Q3 + 1.5 IQR and extreme above Q3 + 3 IQR. The interquartile range is often used to find outliers in data. Outliers here are defined as observations that fall below Q1 − 1.5 IQR or above Q3 + 1.5 IQR.

  4. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    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)

  5. Sample maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Sample_maximum_and_minimum

    Box plots of the Michelson–Morley experiment, showing sample maxima and minima. 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]

  6. Summary statistics - Wikipedia

    en.wikipedia.org/wiki/Summary_statistics

    Box plot of the Michelson–Morley experiment, showing several summary statistics. 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

  7. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    Box plots are non-parametric: they display variation in samples of a statistical population without making any assumptions of the underlying statistical distribution, thus are useful for getting an initial understanding of a data set. For example, comparing the distribution of ages between a group of people (e.g., male and females).

  8. Candlestick chart - Wikipedia

    en.wikipedia.org/wiki/Candlestick_chart

    Candlestick charts are thought to have been developed in the 18th century by Munehisa Homma, a Japanese rice trader. [2] They were introduced to the Western world by Steve Nison in his book Japanese Candlestick Charting Techniques, first published in 1991.

  9. Mary Eleanor Spear - Wikipedia

    en.wikipedia.org/wiki/Mary_Eleanor_Spear

    Mary Eleanor Hunt Spear (March 4, 1897 – January 22, 1986) was an American data visualization specialist, graphic analyst and author, who pioneered development of the bar chart and box plot. Early life and education

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