Line graphs are the Swiss army knives of data visualisation. They can be almost anything… which is both good and bad.
Line graphs are slow to interpret
Many graphs serve one clear purpose. Take the five graphs below:
Even without labels, it’s clear what role each of these graphs serves:
- Pie chart—components of a total
- Thermometer—progress toward a goal amount
- Speedometer—percentage of the largest possible value
- Histogram—distribution of values
- Box plot—statistical summaries of several datasets
In other words, if I’m presented with one of the graphs above, I have an immediate head start on interpreting it. If, instead, I’m presented with a line graph, I’m forced to read the axes labels and limits first.
Deciphering text is the slow way to intake information. Shape is fastest, then colour, and only then text. This so-called Sequence of Cognition, popularised by Alina Wheeler, is something marketers need to know about.
Continue reading “Line graphs: the best and worst way to visualise data”
Brushing Up Science 