Measures of Position – Quartiles, IQR, Percentiles
Measures of position tell where a value lies relative to the rest of the data.
For ungrouped (raw) data we often use quartiles,
the interquartile range (IQR), percentiles,
and percentile rank.
Quartiles
Quartiles divide a ranked data set into four equal parts:
- First quartile Q1: 25% of the data are less than Q1.
- Second quartile Q2: 50% of the data are less than Q2 (this is the median).
- Third quartile Q3: 75% of the data are less than Q3.
Procedure for ungrouped data (the rule used in this tool):
- Rank all observations in increasing order.
- Find the median of all values – this is Q2.
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Form the lower half and the upper half of the data:
if the number of values n is odd, omit the median from both halves;
if n is even, split into two equal halves.
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Q1 is the median of the lower half, and
Q3 is the median of the upper half.
Interquartile range (IQR)
The interquartile range measures the spread of the middle 50% of the data:
Percentiles
Percentiles divide a ranked data set into 100 equal parts. The
kth percentile, written Pk, is a value such that
approximately k% of the observations are less than or equal to it and
(100 − k)% are greater.
For ungrouped data with n values, an approximate position for
Pk is found by
Percentile rank
The percentile rank of a value xr is the percentage of data
values that are less than xr:
Interpreting this rank tells you what proportion of the data falls below that value
(for example, “xr is at about the 67th percentile of this data set”).