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  2. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    The lower quartile corresponds with the 25th percentile and the upper quartile corresponds with the 75th percentile, so IQR = Q 3 − Q 1 [1]. The IQR is an example of a trimmed estimator , defined as the 25% trimmed range , which enhances the accuracy of dataset statistics by dropping lower contribution, outlying points. [ 5 ]

  3. Interquartile mean - Wikipedia

    en.wikipedia.org/wiki/Interquartile_mean

    The interquartile mean (IQM) (or midmean) is a statistical measure of central tendency based on the truncated mean of the interquartile range.The IQM is very similar to the scoring method used in sports that are evaluated by a panel of judges: discard the lowest and the highest scores; calculate the mean value of the remaining scores.

  4. 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.

  5. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    The five-number summary gives information about the location (from the median), spread (from the quartiles) and range (from the sample minimum and maximum) of the observations. Since it reports order statistics (rather than, say, the mean) the five-number summary is appropriate for ordinal measurements, as well as interval and ratio measurements.

  6. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    The only 2-quantile is called the median; The 3-quantiles are called tertiles or terciles → T; 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

  7. 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.

  8. Needs assessment - Wikipedia

    en.wikipedia.org/wiki/Needs_assessment

    A needs assessment is a systematic process for determining and addressing needs, or "gaps", between current conditions, and desired conditions, or "wants". [ 1 ] Needs assessments can help improve policy or program decisions, individuals, education, training, organizations, communities, or products.

  9. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    The first quartile (Q 1) is defined as the 25th percentile where lowest 25% data is below this point. It is also known as the lower quartile. The second quartile (Q 2) is the median of a data set; thus 50% of the data lies below this point. The third quartile (Q 3) is the 75th percentile where