Charts lie all the time. Not through fabricated data, but through design choices that distort perception: truncated axes, cherry-picked time ranges, misleading scales, and 3D effects that warp proportions. Understanding these techniques doesn't just help you spot manipulation — it makes you a better communicator when you create visualizations yourself.
The truncated Y-axis
This is the most common chart crime. When a bar chart's Y-axis starts at 95 instead of 0, a 1% difference looks like a 100% difference visually. Politicians and advertisers use this constantly to make small changes look dramatic. The fix: always check where the axis starts, and be suspicious of any chart where the bars don't start at zero.
Cherry-picked time ranges
Select the right start and end date, and almost any trend can be made to look like growth or decline. A company showing its stock performance "since our low point in March" rather than year-over-year is almost certainly obscuring an unflattering longer-term picture.
Correlation presented as causation
Spurious correlations are everywhere. Nicolas Cage movies released per year correlates almost perfectly with swimming pool drownings. GDP correlates with cheese consumption. These are meaningless — but correlation is visually compelling, which is why it gets abused constantly in data journalism.
What honest visualization looks like
Edward Tufte's principle of data-ink ratio — maximize the proportion of ink that actually represents data — is still the best single rule. Show full scales. Label axes clearly. Don't use 3D. Don't use pie charts with more than five slices. And always include sample size and confidence intervals when presenting statistics.