On spurious correlations

When this came through my inbox this morning, all I could think was, “How have I never found this blog before?” Harvard Business Review has a new article – “Beware Spurious Correlations” – that features the absurd (like an example of how iPhone sales correlates visually with U.S. deaths from falling down stairs) and the serious implications of what that means for those visualizing data and inferring unproven causal relationships.

The teaser from HBR:

“We all know the truism “Correlation doesn’t imply causation,” but when we see lines sloping together, bars rising together, or points on a scatterplot clustering, the data practically begs us to assign a reason. We want to believe one exists.

Statistically we can’t make that leap, however. Charts that show a close correlation are often relying on a visual parlor trick to imply a relationship. Tyler Vigen, a JD student at Harvard Law School and the author of Spurious Correlations, has made sport of this on his website, which charts farcical correlations—for example, between U.S. per capita margarine consumption and the divorce rate in Maine.”

Read the article for the full explanation, but all to say, be thoughtful about how you visualize your data – don’t fall prey to misleading with charts and graphs.

Applying human centered design to data visualization

Jeff Knezovich over at On Think Tanks posted some great reflections from his recent trip to the Cartanga Data Festival, breaking down why data viz isn’t just a science but also an art. Data science alone, with its emphasis on statistics, code, and often technology, can’t develop the kind of simple yet artful visualizations that we find on feature blogs like Information is Beautiful or in reports to Ministries of Health that effectively advocate for new health facilities.

One of the highlights of his post was insight into how he approaches data visualization training and design as a discipline that requires expertise in research, technology, design, and communication.  Jeff unpacks (with some great resource links!) the importance of design from a visual and graphical sense, but I would argue that data viz design requires a certain level of understanding of the human experience of interacting with information. Who is your audience? How do they interact with information? What is their level of numeric literacy? How much do they care about the information you’re trying to communicate?

My team has been exploring human centered design (HCD) methods through our work on the Innovations for Maternal, Newborn,, and Child Health Initiative*. At the core, HCD focuses on developing an empathy with the beneficiaries of a program. In visualization design, identifying an audience for your visualization and keeping them at the center of your design process is key to creating something that makes information meaningful.

Applying these principles of design need not be onerous or feel intimidating for data visualization designers (though the facilitation guides and experts in this space can go deep in more involved program design). Next time you’re crafting something visual from a data set, think about these three things:

  1. Who am I creating this for? As yourself this question repeatedly throughout the design process, not just at the very beginning. Understand both what they say they need from your analysis, but also their latent needs and expectations. If you’re working on a more complex project, like developing a dashboard, creating personas for your different users could be very helpful.
  2. Prototype (sketch!), test, and iterate. Don’t be afraid to ask for feedback from your users or at the very least your colleagues throughout the design process. And don’t be afraid to make changes!
  3. How will my audience use this product? How will your audience feel when they see your graph, chart, infographic, video, or dashboard? How they will interpret and use the data analysis you’ve presented? These considerations are key to ensuring your visualizations are used to promote evidence-led decision making.

Have you deliberately applied principles of human centered design in your data viz design? Share your experiences & learning in the comments!

*The Innovations Initiative is led by Concern Worldwide and funded by the Bill & Melinda Gates Foundation. JSI serves as the global research partner for the project.