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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. Sample maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Sample_maximum_and_minimum

    The sample maximum and minimum are the least robust statistics: they are maximally sensitive to outliers.. This can either be an advantage or a drawback: if extreme values are real (not measurement errors), and of real consequence, as in applications of extreme value theory such as building dikes or financial loss, then outliers (as reflected in sample extrema) are important.

  4. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    If data are placed in order, then the lower quartile is central to the lower half of the data and the upper quartile is central to the upper half of the data. These quartiles are used to calculate the interquartile range, which helps to describe the spread of the data, and determine whether or not any data points are outliers.

  5. 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.

  6. Outlier - Wikipedia

    en.wikipedia.org/wiki/Outlier

    Box plot of data from the Michelson–Morley experiment displaying four outliers in the middle column, as well as one outlier in the first column. In statistics, an outlier is a data point that differs significantly from other observations.

  7. Kurtosis - Wikipedia

    en.wikipedia.org/wiki/Kurtosis

    Specifically, it reflects either the presence of existing outliers (for sample kurtosis) or the tendency to produce outliers (for the kurtosis of a probability distribution). The underlying logic is straightforward: Kurtosis represents the average (or expected value) of standardized data raised to the fourth power. Standardized values less than ...

  8. Anscombe's quartet - Wikipedia

    en.wikipedia.org/wiki/Anscombe's_quartet

    The four datasets composing Anscombe's quartet. All four sets have identical statistical parameters, but the graphs show them to be considerably different. Anscombe's quartet comprises four datasets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed.

  9. Data and information visualization - Wikipedia

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

    Box and whisker plot: Box and Whisker Plot: x axis; y axis; A method for graphically depicting groups of numerical data through their quartiles. Box plots may also have lines extending from the boxes (whiskers) indicating variability outside the upper and lower quartiles. Outliers may be plotted as individual points.