Now let’s substitute a data visualization—specifically the line chart in Figure 0.1—in place of the table, to compare which one is more persuasive.
Is Figure 0.1 more persuasive than Table 0.1? Since the line chart contains the same historical start and stop points as the table, it should not make any difference. But the line chart also communicates a powerful, visualized data story about income gaps that grabs your attention more effectively than the table. As your eyes follow the colored lines horizontally across the page, the widening inequality between the top versus the middle and bottom tiers is striking. The chart also packs so much granular information into one image. Looking closely, you also notice how the top-tier income level was relatively stable during the 1970s, then spiked upward from the 1980s to the present, and grew more distant from other lines. Meanwhile, as the middle-tier income rose slightly over time, the fate of the lowest-tier remained relatively flat, reached its peak in 2007, and then dipped back downward for much of the past decade. The rich got richer, and the poor got poorer, as the saying goes. But the chart reveals how rapidly those riches grew, while poverty remained recalcitrant in recent years.
Now let’s insert Figure 0.2, which contains the same data as Figure 0.1, but presented in a different format. Which chart should you believe? Remember, we warned you to watch out for people who use data visualizations to tell lies.
What’s going on? If Figure 0.2 contains the same data as Figure 0.1, why do they look so different? What happened to the striking growth in inequality gaps, which now seem to be smoothed away? Did the crisis suddenly disappear? Was it a hoax?
Although the chart in Figure 0.2 is technically accurate, it intentionally misleads readers. Look closely at the labels in the vertical axis. The distance between the first and second figures ($1,000 to $10,000) is the same as the distance between the second and the third ($10,000 to $100,000), but those jumps represent very different amounts of money ($9,000 versus $90,000). That’s because this chart was constructed with a logarithmic scale, which is most appropriate for showing exponential growth. You may recall seeing logarithmic scales during the Covid pandemic, when they were appropriately used to illustrate very high growth rates, which are difficult to display with a traditional linear scale. This second chart is technically accurate, because the data points and scale labels match up, but it’s misleading because there is no good reason to interpret this income data using a logarithmic scale, other than to deceive us about this crisis. People can use charts to illuminate the truth, but also can use them to disguise it.