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  2. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    The three quartiles, resulting in four data divisions, are as follows: 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.

  3. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    First quartile The rank of the first quartile is 10×(1/4) = 2.5, which rounds up to 3, meaning that 3 is the rank in the population (from least to greatest values) at which approximately 1/4 of the values are less than the value of the first quartile. The third value in the population is 7. 7 Second quartile

  4. 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 ]

  5. 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) the lower quartile or first quartile; the median (the middle value) the upper quartile or third quartile; the sample maximum (largest observation)

  6. Ranking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Ranking_(statistics)

    In statistics, ranking is the data transformation in which numerical or ordinal values are replaced by their rank when the data are sorted. For example, the ranks of the numerical data 3.4, 5.1, 2.6, 7.3 are 2, 3, 1, 4.

  7. 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 ...

  8. Quantile function - Wikipedia

    en.wikipedia.org/wiki/Quantile_function

    In probability and statistics, the quantile function outputs the value of a random variable such that its probability is less than or equal to an input probability value. Intuitively, the quantile function associates with a range at and below a probability input the likelihood that a random variable is realized in that range for some ...

  9. 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 ...