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  2. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    In statistics, quartiles are a type of quantiles which divide the number of data points into four parts, or quarters, of more-or-less equal size. The data must be ordered from smallest to largest to compute quartiles; as such, quartiles are a form of order statistic. The three quartiles, resulting in four data divisions, are as follows:

  3. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    The first quartile is determined by 11×(1/4) = 2.75, 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

    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

  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. Box plot - Wikipedia

    en.wikipedia.org/wiki/Box_plot

    The first quartile value can be easily determined by finding the "middle" number between the minimum and the median. For the hourly temperatures, the "middle" number found between 57°F and 70°F is 66°F. The third quartile value (Q 3 or 75th percentile) is the number that marks three quarters of the ordered data set. In other words, there are ...

  7. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    In statistics, dispersion (also called variability, scatter, or spread) is the extent to which a distribution is stretched or squeezed. [1] Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range. For instance, when the variance of data in a set is large, the data is widely scattered.

  8. Regions Financial (RF) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/finance/regions-financial-rf-q4-2024...

    This morning, we reported strong full-year earnings of $1.8 billion, resulting in earnings per share of $1.93, and a top quartile return on average tangible common equity of 18%.

  9. 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 ...