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  2. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    Boxplot (with an interquartile range) and a probability density function (pdf) of a Normal N(0,σ 2) Population. In descriptive statistics, the interquartile range (IQR) is a measure of statistical dispersion, which is the spread of the data. [1] The IQR may also be called the midspread, middle 50%, fourth spread, or H‑spread.

  3. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    where ⁡ is the interquartile range of the data and is the number of observations in the sample . In fact if the normal density is used the factor 2 in front comes out to be ∼ 2.59 {\displaystyle \sim 2.59} , [ 4 ] but 2 is the factor recommended by Freedman and Diaconis.

  4. Robust measures of scale - Wikipedia

    en.wikipedia.org/wiki/Robust_measures_of_scale

    One of the most common robust measures of scale is the interquartile range (IQR), the difference between the 75th percentile and the 25th percentile of a sample; this is the 25% trimmed range, an example of an L-estimator. Other trimmed ranges, such as the interdecile range (10% trimmed range) can also be used.

  5. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    Interquartile range (IQR) is defined as the difference between the 75th and 25th percentiles or Q 3 - Q 1. While the maximum and minimum also show the spread of the data, the upper and lower quartiles can provide more detailed information on the location of specific data points, the presence of outliers in the data, and the difference in spread ...

  6. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    The 4-quantiles are called quartiles → Q; the difference between upper and lower quartiles is also called the interquartile range, midspread or middle fifty → IQR = Q 3 − Q 1. The 5-quantiles are called quintiles or pentiles → QU; The 6-quantiles are called sextiles → S; The 7-quantiles are called septiles → SP; The 8-quantiles are ...

  7. L-estimator - Wikipedia

    en.wikipedia.org/wiki/L-estimator

    Simple L-estimators can be visually estimated from a box plot, and include interquartile range, midhinge, range, mid-range, and trimean. In statistics, an L-estimator (or L-statistic) is an estimator which is a linear combination of order statistics of the measurements. This can be as little as a single point, as in the median (of an odd number ...

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  9. Robust statistics - Wikipedia

    en.wikipedia.org/wiki/Robust_statistics

    The median absolute deviation and interquartile range are robust measures of statistical dispersion, while the standard deviation and range are not. Trimmed estimators and Winsorised estimators are general methods to make statistics more robust.