quartile

n.

The value of the boundary at the 25th, 50th, or 75th percentiles of a frequency distribution divided into four parts, each containing a quarter of the population.

[Middle English, 90 degrees apart (of the relative position of two celestial bodies), from Old French quartil, from Medieval Latin quārtīlis, of a quartile, from Latin quārtus, fourth. See quart.]

If a set of numerical data has n elements and is arranged in increasing order

the lower quartile (Q₁) may be taken to be the median of the lower half of the data, i.e. of x₁, x₂,..., x_½(n−1) if n is odd, and the median of x₁, x₂,..., x_½n if n is even. The upper quartile (Q₃) may be taken to be the median of the upper half of the data, i.e. of x_½(n+1), x_½(n+3),..., x_n if n is odd, and the median of x_½(n+2), x_½(n+4),..., x_n if n is even. The difference Q₃−Q₁ is the interquartile range, a term introduced by Galton in 1882. An alternative term is the midspread.

As an example, consider the ordered data:

101, 103, 104, 105, 106, 107, 108, 109, 111, 111, 111, 115, 118, 121, 124, 127, 130, 156, 199.

There are nineteen observations. The tenth largest is 111, the median. Within the lower nine values, the fifth largest is 106 (=Q₁). Within the upper nine values the fifth largest is 124 (=Q₃). The inter-quartile range is 124−106=18.

When there are many observations it may be easier to read approximate values for the lower and upper quartiles from a cumulative frequency graph. These will be the values of the variable corresponding to cumulative relative frequencies of 25% and 75%, respectively.

For a continuous random variable X, the lower quartile of the distribution is such that P(X<Q₁)=¼ and the upper quartile is such that P(X<Q₃)=¾.

In his 1970 book on exploratory data analysis, Tukey referred (in the context of data) to the quartiles as hinges and he called the interquartile range the H-spread. Tukey defined a step as 1.5 × H-spread, and proposed that values one step beyond a hinge should be called inner fences and values two steps beyond a hinge should be called outer fences. Any data item beyond an outer fence would be called far out.

In the previous data the hinges are 106 and 124, thus the H-spread is 124−106=18 and the step is 1.5 × 18=27. The inner fences are at 106−27=79 and 124+27=151. The outer fences are at 79−27=52 and 151+27=178. The observation 199 is greater than 178 and is therefore far out.

See also boxplot; outlier; quantile; skewness; trimean.

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A statistical term describing a division of observations into four defined intervals based upon the values of the data and how they compare to the entire set of observations.

Investopedia Says:
Each quartile contains 25% of the total observations. Generally, the data is ordered from smallest to largest with those observations falling below 25% of all the data analyzed allocated within the 1st quartile, observations falling between 25.1% and 50% and allocated in the 2nd quartile, then the observations falling between 51% and 75% allocated in the 3rd quartile, and finally the remaining observations allocated in the 4th quartile.

Try not to confuse a quarter with a quartile.

Statistical measurement. The first quartile of a list is the number that has three quarters of the numbers in the list below it; the fourth quartile is the number that has three quarters of the numbers above it; the second quartile is the same as the median.

statistics A form of quantile; divides the range into quarters.

One of the values establishing the division of a series of variables into fourths, or the range of items included in such a segment.

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