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  2. Decile - Wikipedia

    en.wikipedia.org/wiki/Decile

    In descriptive statistics, a decile is any of the nine values that divide the sorted data into ten equal parts, so that each part represents 1/10 of the sample or population. [1] A decile is one possible form of a quantile ; others include the quartile and percentile . [ 2 ]

  3. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    Fourth quartile Although not universally accepted, one can also speak of the fourth quartile. This is the maximum value of the set, so the fourth quartile in this example would be 20. Under the Nearest Rank definition of quantile, the rank of the fourth quartile is the rank of the biggest number, so the rank of the fourth quartile would be 10. 20

  4. 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

  5. Percentile - Wikipedia

    en.wikipedia.org/wiki/Percentile

    The 25th percentile is also known as the first quartile (Q 1), the 50th percentile as the median or second quartile (Q 2), and the 75th percentile as the third quartile (Q 3). For example, the 50th percentile (median) is the score below (or at or below, depending on the definition) which 50% of the scores in the distribution are found.

  6. Seven-number summary - Wikipedia

    en.wikipedia.org/wiki/Seven-number_summary

    The middle three values – the lower quartile, median, and upper quartile – are the usual statistics from the five-number summary and are the standard values for the box in a box plot. The two unusual percentiles at either end are used because the locations of all seven values will be approximately equally spaced if the data is normally ...

  7. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    It is defined as the difference between the 75th and 25th percentiles of the data. [2] [3] [4] To calculate the IQR, the data set is divided into quartiles, or four rank-ordered even parts via linear interpolation. [1] These quartiles are denoted by Q 1 (also called the lower quartile), Q 2 (the median), and Q 3 (also called the

  8. 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.

  9. Percentile rank - Wikipedia

    en.wikipedia.org/wiki/Percentile_rank

    The figure illustrates the percentile rank computation and shows how the 0.5 × F term in the formula ensures that the percentile rank reflects a percentage of scores less than the specified score. For example, for the 10 scores shown in the figure, 60% of them are below a score of 4 (five less than 4 and half of the two equal to 4) and 95% are ...