Making data make sense

I recently found a website called “Our World in Data,” a repository of lots of varied and valuable information, which I look forward to exploring. For today, I highlight a couple of charts that each say interesting things, and that say another interesting thing when considered together.

Recognizing that our ability to evaluate conditions around the world is enhanced by having an understanding of the history involved, the site’s founding author, Max Roser, provides this chart representing the percentage of the world’s people living in extreme poverty (defined as $1.90 per day) during the period from 1820 to 2015. That income figure is standardized across different countries, and adjusted for inflation over time.

This looks to me like very good news. Beginning with almost 90% of the world’s people living in abject poverty in 1820, that number is now well below 20%. That number is much higher than ideal, but look at the trend line—in context, it’s cause for celebration.

At the bottom left of the graphic on the website, I noticed a little button labeled “Relative.” When I toggled the button so it was no longer checked, I got a whole new picture.


These two pictures look radically different, but they’re representing the same data in two different ways. What we see in this second picture is the same relationship between the desperately poor and those with more resources. The 1820 ratio is still about 90% of the people in extreme poverty, and the 2015 ratio shows less than 20% in that category.

The big change, of course, is that now we’re not just looking at the relationship between the haves and the have-hardly-anything group. We’re looking at the size of those groups. In the top chart, it appears that there’s just an enormous number of desperately poor people in 1820, and as time passes, more and more people are in a better financial position.

The second chart shows me that the number of people living in extreme poverty is actually growing over time, though not quickly, and that the absolute number doesn’t drop below 1820 levels until sometime around 2010.

The fascinating message I get from considering both these pictures together is that in addition to the many ways there are to represent numbers, there are many ways for me to misunderstand or misinterpret what I’m seeing; reading all the fine print is key to making sure I know what I’m looking at.

Scholars representing data visually don’t bear total responsibility for me properly interpreting their charts. But they’ll be more effective in getting their message across if they go beyond trying to help me understand and focus on making it hard to misunderstand.


In contrast, some charts are quite easy to understand.


For my part, perhaps I should be talking to myself more. After reading the fine print, saying out loud, “This huge red area shows me the percentage of people in poverty, not the absolute number of people in poverty,” could help me keep things straight in my mind.

Helping people make sense of data can be difficult at the best of times, and using visual means to communicate statistical relationships is complicated. Do you have examples of cases where it’s done well, or done impressively badly?


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