Confidence intervals or error bars are lines or shading extending from data values to show variability or uncertainty in these values. Wide or long error bars indicate more uncertainty.

Error bars are not used consistently across scientific disciplines. This means that readers’ ability to recognise and understand error bars will differ.

Accordingly, if variability or uncertainty in your data values is not a focus of the graph or your data message, it may be best to present the data without error bars. If variability or uncertainty is a focal point, make sure these aspects of the data are discussed in the text, and that error bars or shading are explained in the notes section underneath the graph. This enables you to explain the role of error in the results, rather than leaving the reader to potentially misinterpret the graphical display of error.

Shading designs may convey error to readers more accurately and less distractingly than lines protruding from individual data values (Correll & Gleicher 2014).