I’m aware of the ecological fallacy and amalgamation paradoxes. I describe them in later books! However, the obesity vs. education graphic isn’t a good example of them, I believe. According to researchers I consulted, the association exists down to the individual level (it’s weaker, but this common when we aggregate or disaggregate data). In general, and with obvious exceptions, the more educated a person is, the less likely he or she is to be obese; the causal links are very complicated, of course. This may end up being wrong, but it’s what I got from experts (1).
Another matter is the wording I used. I agree with you that this needs attention, as the description I wrote of what the charts show is sloppy. If I remember well, the first time you sent me your articles I thanked you for pointing it out.
Throughout the years I’ve become more aware of how important it is to correctly describe what a chart shows, as doing it wrong may bias our perception of them. In this case, a better wording would be “at the state level there’s a positive association between education and obesity —and vice versa; but that doesn’t mean that the association is causal, and it may disappear or even reverse at lower levels of aggregation”. Clunkier, but perhaps closer to the truth.
Why didn’t I refer to confounders, ecological fallacies, amalgamation/Simpson’s paradoxes, causality, etc. in that section? This is essential to understanding why I think your critiques are a bit off, although I still consider them valid and useful: ‘The Functional Art’ isn’t a book about analytics or reasoning. It’s about the visual design of charts and infographics: choosing graphic forms, colors, typography, layout, and so forth.
Can we separate one from the other? You’ll argue that we can’t, and we can have a chat about it at some point. However, and as in the rest of the book, I didn’t make an assertion based on data myself, as I didn’t analyze anything. The education vs. obesity exercise is simply based on taking *somebody else’s* assertion and think about how to visualize it in different ways. In fact, that example appears in a chapter about visual perception and Cleveland’s scale of encodings.
(1) I do this in all books, as I’m painfully aware of my own knowledge gaps, and terrified of mistakes. I’m no statistician and, as you write, quoting Taleb, “statistics are hard”. I couldn’t agree more. In ‘The Truthful Art’, even if I discuss some elementary summary stats, my main recommendation —which I hammer constantly— is to “always consult with experts”.