As I started reading The Book of Why: The New Science of Cause and Effect, by Judea Pearl and Dana Mackenzie (Basic Books, 2018), I was reminded how often analysts trot out the bromide “correlation is not causation.” It’s a well-known warning. Indeed, I often encourage those learning data visualization to ensure their designs don’t imply causation. But this book helped me think more deeply about it.

This is not a light read—but it is an important one. As Pearl and Mackenzie make so clear in case studies, causation is central to how we think as human beings. Most nonstatisticians are not really interested in patterns and correlations in the data. They want to know what causes an effect so they can take appropriate action.

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