In descriptive statistics, a quartile is one of the three values which divide the sorted data set into four equal parts.
Thus:
Often it is necessary to interpolate between data values to accomplish this, as in the following example.
If the sample size[?] is not a multiple of four, some of the quartiles may be numbers in the original data set, as in this example:
In both of the above cases, the first and third quartiles can be taken to be the median values of the lower and upper halves of the data, respectively. However, there are two schools of thought on how to apply this definition when the overall median is one of the original data values.
One may include the median in both "halves" of the data:
Or not include the median in either "half":
More precise mathematical formulations are possible....
The difference between the upper and lower quartiles is called the interquartile range.
See also: Summary statistics, Quantile, Percentile[?]
i x[i]
1 102
2 105
------------- first quartile, Q1 = (105+106)/2 = 105.5
3 106
4 109
------------- second quartile, Q2 = (109+110)/2 = 109.5
5 110
6 112
------------- third quartile, Q3 = (112+115)/2 = 113.5
7 115
8 118
i x[i]
1 102
2 105 -- Q[1] = 105
3 106
------------- Q[2] = 107.5
4 109
5 110 -- Q[3] = 110
6 112
i x[i]
1 102
2 105
3 106 -- Q1 = 106
4 109
5 110
)- Q2 = 110 (note line 5 has been duplicated
5 110 to illustrate the point)
6 112
7 115 -- Q3 = 115
8 118
9 120
i x[i]
1 102
2 105
------------- Q1 = 105.5
3 106
4 109
5 110 -- Q2 = 110
6 112
7 115
------------- Q3 = 116.5
8 118
9 120