Boxplots in Jamovi

Cheatsheet

Published

August 4, 2026

This work was developed using resources that are available under a Creative Commons Attribution 4.0 International License, made available on the SOLES Open Educational Resources repository by the School of Life and Environmental Sciences, The University of Sydney.

About

The boxplot is a visual representation of a dataset’s distribution, showing the median, quartiles, and outliers. It is useful for comparing distributions between groups and identifying outliers within a single group.

  • You have Jamovi installed ideally 2.5.7.0 or later.
  • You can follow instructions to select, click and drag elements in Jamovi.

The data should be in a long format (also known as tidy data), where each row is an observation and each column is a variable (Figure 1). If your data is not already structured this way, reshape it manually in a spreadsheet program or in R using the pivot_longer() function from the tidyr package.

Sex BW
F 2.15
M 2.55
F 2.95
F 2.70
M 2.20
F 1.85
M 2.55
M 2.60

 

F M
2.15 2.55
2.95 2.20
2.70 2.55
1.85 2.60
Figure 1: Data should be in long format (left) where each row is an observation and each column is a variable. This is the preferred format for most statistical software. Wide format (right) is also common, but may require additional steps to analyse or visualise in some instances.

Data

For this cheatsheet we will use part of the possums dataset used in BIOL2022 labs.

Import data

  1. Click on the Menu icon:
  2. Select Open > Browse, and navigate to the downloaded file.
  3. Click Open to load the data.

Plot

  1. Click on the Analyses tab.
  2. Select Exploration > Descriptives.
  3. Add Sex to the “Split by” box.
  4. Add BW to the “Variables” box.
  5. In the “Plots” tab, select Boxplot.
Figure 2: How to import data and create a boxplot in Jamovi. Click on the image to expand it.

Export

To export the plot, right click on the plot, select Image > Export… > Browse and rename the file before clicking on the Save button.

Figure 3: A popup window should appear when you right click on a plot, where you can export the image. Click on the image to expand it.