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Percentiles & Quartiles

Converting magnitude into position makes it possible to compare values across different distributions.

To decide whether a score of 82 is high, you need to know the test difficulty and how everyone else scored. If most students scored above 90, 82 is relatively low; if most scored between 50 and 70, it may be very high.

A raw score tells you the magnitude of a value. A percentile tells you where that value stands within a reference distribution.

Key question

How can we express the position of one value within the full set of observations?

1

Concept

What does a percentile mean?

A percentile is a relative position in ordered data

The 90th percentile means that about 90% of the observations in the reference group are at or below that value. It places the value near the top 10%; it does not mean that the raw score is 90.

ExpressionMeaning
90%a proportion of 90 out of 100
90 pointsthe original measured score
90th percentilea position at or above roughly 90% of the reference group

Percentile value vs. percentile rank

Some textbooks and software distinguish the value at a given percentile from the percentile rank of an observed value.

2

Why It Matters

How do quartiles divide the data?

Quartiles divide ordered data into four sections

MeasurePositionMeaning
Q125th percentileabout 25% are at or below this value
Q250th percentilethe median
Q375th percentileabout 75% are at or below this value
IQRQ3−Q1width of the middle 50%

Software packages use slightly different conventions for calculating quartiles. In small samples, Q1 and Q3 may differ across methods, so reporting the method can be helpful.

3

How It Works

Why is the IQR resistant to extremes?

The IQR focuses on the middle half rather than the endpoints

IQR=Q3−Q1 does not use the minimum and maximum directly. As a result, one extremely large observation usually changes it much less than it changes the range.

Potential-outlier rule

Boxplots commonly flag values below Q1−1.5×IQR or above Q3+1.5×IQR as potential outliers.

Not an automatic deletion rule

A value beyond 1.5×IQR is an observation to investigate, not automatically an error that should be removed.

4

Example

How do raw score and position differ?

The same raw score can occupy a different position in a different reference group

Reference distributionInterpretation of 82
Most scores are 90–100low percentile
Most scores are 50–70high percentile
Scores are widely dispersedpossibly moderately high

Percentiles are useful for comparing relative position across tests, growth charts, or income distributions with different units and shapes. They do not preserve the actual distance between values.

5

Interactive

Move the score

Move the score

Start with a value near the middle and inspect its percentile rank. Then move it up and down to see why equal score changes do not always produce equal rank changes.

Q1

55

Q2

70

Q3

82

Percentile rank

53%

424851555962667074788286919598

8 values are at or below 72.

What to notice

In a dense part of the distribution, a small score change can move the percentile substantially. In a sparse region, a larger score change may barely change the position.

Key takeaways

  • A percentile describes position in ordered data rather than absolute magnitude.
  • Q1, Q2, and Q3 correspond to the 25th, 50th, and 75th percentiles.
  • The IQR is the width of the middle 50% and is relatively resistant to extremes.
  • Percentiles support position comparisons but discard some information about actual distances between values.
Next: Skewness & Kurtosis