---
title: "Boxplots with outliers"
slug: "showing-outliers"
updated: 2023-11-28T07:19:04Z
published: 2023-11-28T07:19:04Z
canonical: "userguide.dataclassroom.com/showing-outliers"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://userguide.dataclassroom.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Showing outliers

"Outliers" is a word used to describe data points that lie **unusually far from the general grouping of the other points** ([see below](https://portal.document360.io/v1/docs/showing-outliers#what-not-to-do-with-outliers) for more detail).

These can be **highlighted visually** by showing the general distribution of the data as a descriptive statistics annotation - such as a **box-and-whiskers** (aka boxplot) or a dot-and-error-bars - and then just showing the data points that are calculated to be outliers, like this:

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1701086062399.png)

DataClassroom can show outliers as determined by one of the following methods:

- The **1.5 IQR rule**. Outliers are data points which are above the 75% percentile of the data plus 1.5 times the distance between the 25% and 75% percentiles (the "IQR"), as seen on a boxplot. And those that are correspondingly below the 25% percentile minus 1.5 x IQR.
- The **2SD rule**. Outliers are those which are further from the mean than 2 x the standard deviation. Usually seen on a plot showing the mean and standard deviation.

IQR stands for **Interquartile Range**, which is the distance from the 25th percentile to the 75th percentile.

### How to show outliers

While showing descriptive stats, select **Show outliers** under the Show dots options:![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1701077710507.png)

You will be asked which method you want to choose:

![](https://cdn.document360.io/62f8f41e-e041-42c4-b9bc-8ae1eb45d064/Images/Documentation/image-1701078313408.png)

When you click Confirm:

- If you chose 1.5 IQR, your [descriptive statistics](/v1/docs/descriptive-statistics) setting will be set to "median-based" and the whiskers on the boxplot will show the 1.5 IQR range.
- If you chose 2 SD, the setting will be "mean-based" and the whiskers will show the 2SD range.

### What (not) to do with outliers?

It is important to realize that there is **nothing special about the 1.5 IQR range**, or the points that lie outside this range. It is an arbitrary range, but it was decided upon by John Tukey, the inventor of the [box plot](https://en.wikipedia.org/wiki/Box_plot). And it has been widely used, especially when graphs were drawn with pencil and paper and drawing all the dots was too much like hard work, so a box-and-whiskers plot was used. We recommend showing all your data points in the dot plot, rather than replacing them with a box-and-whiskers representation.

**Outlier points may well be perfectly valid data points**, just ones that lie unusually far from the rest. DataClassroom will include them in all its calculations.

If you see a point that you realize lies far from the rest **and you know a reason that makes it invalid** (for example, someone has taken a temperature reading with a broken thermometer), then we recommend that you [exclude the data point](/v1/docs/excluding-rows-of-data) from your data set - and maybe make a note that you did that.