This section discusses percentiles, which are useful for describing relative standings of observations in a dataset.


Learning Objectives

  1. Define percentiles
  2. Use three formulas for computing percentiles

A test score in and of itself is usually difficult to interpret. For example, if you learned that your score on a measure of shyness was 35 out of a possible 50, you would have little idea how shy you are compared to other people. More relevant is the percentage of people with lower shyness scores than yours. This percentage is called a percentile. If 65% of the scores were below yours, then your score would be the 65th percentile.

Source: David M. Lane,
Public Domain Mark This work is in the Public Domain.