Lie Factor: Quantifying Visual Distortion in Graphs
The Lie Factor measures how much a graph's visuals distort the data's story. It's used to critique charts that exaggerate changes, like with a truncated y-axis.
The mental model
A graph's visual change should be directly proportional to the numerical change in the data it represents. The Lie Factor is a simple calculation to check this principle: it is the size of the effect shown in the graphic divided by the size of the effect in the data. An honest graph has a Lie Factor close to 1.0.
How it works
To calculate the Lie Factor, you first find the percentage change in the data, such as ((new_value - old_value) / old_value). Then, you measure the percentage change of the physical elements in the graphic representing that data, like the length of two bars. The Lie Factor is the second value divided by the first. A factor greater than 1.05 is 'overstating' the data, while a factor less than 0.95 is 'understating' it. Values between 0.95 and 1.05 are considered acceptable, allowing for minor plotting inaccuracies.
When to use it
Use the Lie Factor as a tool to critically analyze data visualizations, especially in dashboards, business reports, and news articles where graphics can influence important decisions. It provides a concrete number to justify why a chart feels misleading. It is particularly useful for exposing distortion in bar charts, line charts, and pictograms.
When not to use it
The Lie Factor is a heuristic for a specific kind of distortion and not a universal measure of graph quality. It's less applicable to complex visualizations like scatter plots or network graphs, which show relationships rather than simple magnitude changes. Confounding design variation with data variation is the core issue, and there are many ways to create a 'bad' graph that the Lie Factor doesn't measure.
One canonical example
A famous example shows a required increase in fuel economy from 18 to 27.5 miles per gallon. The data shows a 53% increase. However, the line drawn in the graphic to represent this change had a length that increased by 783%. The Lie Factor is 783% / 53%, which equals 14.8. The graphic exaggerated the real-world change by nearly fifteen times, likely by starting the y-axis at a value far from zero.
Interview question
Which visualization type is LEAST suited for evaluation using the Lie Factor?
- a.Bar charts
- b.Scatter plotsCorrect
- c.Pictograms
- d.Line graphs
Why? this is the answer
The Lie Factor is designed to measure distortion in visualizations representing magnitude changes, such as bar, line, and pictograms. It is explicitly stated to be less applicable to complex visualizations like scatter plots, which primarily show relationships rather than simple magnitude changes, making it less effective for assessing distortion in such cases.
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