Creating More Effective Graphs
This seminar begins by reviewing human perception and our ability to decode graphical information. It continues by:
- Ranking elementary graphical perception tasks to identify those that we do the best.
- Showing the limitations of many common graphical constructions.
- Demonstrating newer, more effective graphical forms developed on the basis of the ranking.
- Providing general principles for creating effective graphs, as well as metrics on the quality of graphs with a check-list of possible defects.
- Commenting on software packages that produce graphs.
- Comparing the same data using different graph forms so the audience can see how readability depends on the graphical construction used.
- Discussing Trellis Display (a framework for the visualization of multivariate data) and other innovative methods for presenting more than two variables.
- Presenting Mosaic Plots and other graphical methods for categorical data.
Since scales (the rulers along which we graph the data) have a profound effect on our interpretation of graphs, the section on general principles contains a detailed discussion of scales including:
- To include or not to include zero?
- When do logarithmic scales improve clarity?
- What are breaks in scales and how should they be used?
- Are two scales better than one? How can we distinguish between informative and deceptive double axes?
- Can a scale “hide” data? How can this be avoided?
The seminar concludes with additional topics appropriate for the expected audience. Possible topics include deceptive and misleading graphs, graphs that have affected history, how to decorate if appropriate, resolving conflicting advice on data displays, and special requests from the customer.
Participants will learn to:
- Present data more effectively in documents and presentations.
- Display data so that their structure is more apparent.
- Become more critical and analytical when viewing graphs.
INTENDED AUDIENCE: Anyone who creates, edits, or inspects graphs. There are no prerequisites, and no background in statistics is assumed.
DURATION: 1 or 2 days. The two day version includes more exercises and allows time to work on data provided by the participants.