# Outliers

An outlier is a value far from the rest. A common rule marks a value as an outlier if it lies more than 1.5 times the IQR below Q1 or above Q3.

Statistics (university) · Part 01: Describing data · Card 8 of 9 · Last updated 2026-10-19

## Analogy

One basketball player in a Year 7 class stands out from everyone else on a height chart.

## Example

**The 1.5 x IQR rule**

Data: 12,14,15,15,16,18,45
Q1 = 14, Q3 = 18, IQR = 4
Fences: 14 - 6 = 8 and 18 + 6 = 24
45 is above 24: outlier

## In practice

Outliers can be typing errors or real unusual cases, so check them before deleting anything.

## Practice

### Flashcards

- **What is the upper fence for outliers?** Q3 plus 1.5 times the IQR.

## Questions people ask

### Should you always remove outliers from your data?

No. First ask why the value is unusual. A typo, such as a height of 1700 cm, should be corrected or removed. A genuine rare case may be the most interesting finding. Removing points just to get a tidier result is bad practice, so report what you did.

### How does the 1.5 times IQR rule work?

Multiply the IQR by 1.5 and subtract that from Q1 to get the lower fence, then add it to Q3 for the upper fence. Values outside the fences are flagged as outliers. Boxplots draw the flagged points as dots beyond the whiskers.

## Related concepts

- [Quartiles and IQR](https://studyvisually.com/learn/science/statistics-university/statistics-university-part-1/statistics-university-part-1-concept-7)

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