Why are quantiles important in statistics
A quantile defines a certain part of a data set, that is, a quantile defines how many values of a distribution are above or below a certain limit. Particular quantiles are the quartile (quarter), the quintile (fifth) and the percentile (hundredth).
An example: If you divide a distribution into four equal sections, you speak of four quartiles. The first quartile includes all values that are less than a quarter of all values. In the graphical display, the area to the left of the quartile boundary is 25 percent of the total area enclosed by the distribution. The lower two quartiles comprise 50 percent of all distribution values. The interquartile range between the first and third quartile indicates the area in which 50 percent of all values that are distributed around the mean lie.
Please note that the individual definitions in our statistics lexicon are simplified explanations. The aim here is to bring the individual terms closer to the broadest possible user group. In this respect, it is possible that individual definitions do not fully correspond to scientific standards.
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