Quartile vs Percentile

Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.

Quartile

Describing data

A quartile is one of three values that divide an ordered data set into four groups of roughly equal size.

Quartiles split ordered data into four parts, marked by the first quartile Q1Q_1, the median, and the third quartile Q3Q_3. The first quartile is the median of the lower half and the third quartile is the median of the upper half. For example, in 2, 4, 6, 8, 10 the median is 6, so you exclude it and get Q1=3Q_1 = 3 and Q3=9Q_3 = 9. This site uses the median-excluded convention (the TI-84 method), which drops the overall median when the count is odd.

Full entry for quartile

Percentile

Describing data

A percentile is a value at or below which a given percentage of the data falls, so about 90 percent of values lie at or below the 90th percentile.

The kth percentile is the value at or below which about kk percent of the observations lie. For example, if your test score is at the 85th percentile, roughly 85 percent of test-takers scored at or below you. Quartiles are percentiles too: the first quartile is the 25th percentile and the median is the 50th. Percentiles let you compare a single value to a whole distribution without knowing its shape.

Full entry for percentile

Where each one fits in the course