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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:
The third quartile value for the original example above is determined by 11×(3/4) = 8.25, which rounds up to 9. The ninth value in the population is 15. 15 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.
The statistic is easily computed using the first and third quartiles, Q 1 and Q 3, respectively) for each data set. The quartile coefficient of dispersion is the ratio of half of the interquartile range (IQR) to the average of the quartiles (the midhinge): [1] = + = +.
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
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)
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.
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 ...
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.