Introduction to bar charts

Bar charts have many variations. Bar charts can be used to communicate magnitude of any measure (e.g. magnitudes of effect outcomes, probabilities of an event) and comparisons between options as part-to-whole information [Ancker et al. 2006; Kurz-Milcke et al. 2008; Lipkus 2007]. Bar charts may be suitable to be used as a visual communication tool to a large variety of audiences such as the general public through the media, patients, physicians, regulators and other experts.

In order to understand bar charts, users need to recognise that bar charts communicate part-to-whole information i.e. a bar represents the smaller entity (part) in a bar graph constructed from multiple bars (whole). Users also need to understand that the information in a bar chart is represented by the length of the bars. Bar charts often best represent categorical data, or otherwise some assumptions on continuity corrections would have been made if used with continuous data, for example as used with histograms. See also Summary of key points in the Analysis section of the Recommendations.

Many software packages are capable of producing static bar charts (e.g. statistical packages like Stata, R and SAS, Microsoft Excel®, Tableau, IBM Many Eyes, Hiview 3). Bar charts can also be used interactively, for example by allowing users to provide individual response to the underlying model, or by filtering the underlying data according to different subgroups or criteria.