Dos and Don’ts of Data Visualisation
Whether on purpose or not, a statistician can mislead an audience with a chart. This article explains some chart design principles and common mistakes novice data analysts make. Think about the statistical charts you have seen on billboards, in the news, and in research studies. Using these principles as a guide, would you classify any of those charts as misleading? Be sure to take note of the suggestions for successful dashboards.
Make charts correct
Do use proper aspect ratio to minimise dramatic slope effects
The slope of a line chart should be close to 45 degrees for better perception.
In the example below, the same data are presented in three ways. The slope reflects the scales used on the two axes:
However, in some cases there can be legitimate reasons for not sticking to banking to 45 degrees. For example, to analyse the data that reveal certain patterns, which otherwise would not be visible in the 45-degree slope. See example below:
