At least when I was in school, one thing that kept getting hammered home was that people had difficulty understanding graphs. That I didn't see as being an issue, not unless you're talking about something pretty exotic, but if accurate, it seems like it'd be pretty limiting. And I've seen a lot of later articles also saying that a lot of people have trouble with graph comprehension.

googles

https://towardsdatascience.com/numeracy-and-graph-literacy-in-the-united-states-ea2a11251739

Last month, Alessandro Romano, Chiara Sotis, Goran Dominioni, and Sebastián Guidi surveyed 2,000 people to demonstrate that “the public do not understand logarithmic graphs used to portray COVID-19.”

They found that only 41% of participants could correctly answer basic questions about log-scaled graphs (v.s. 84% accuracy for linear-scale).

But the problem is harder than log scales. As you’ll see below, much of “the public” struggle with even the most basic charts and graphs, let alone complex visualizations.

I wish they'd had more statistics. In my high school, they had half a semester as an elective. In my university curriculum, it wasn't a core class (social science majors would study it, I would guess).

I have explained basic sampling to a ton of people on Reddit when polls came up, because they didn't believe that a sample of 1000 people out of a much larger population could result in a representative outcome. We see poll data all the time. Even if you never perform a poll, understanding the mechanism at least enough to trust it and understand when a poll might not be representative (e.g. self-selecting Internet polls). Confidence levels. I think I covered regressions in high school in an (elective) physics class, not even in a statistics class. That's a useful skill -- get a bunch of numbers, be able to produce a formula to predict more of them and get an idea of how accurate your model is. I assume that if you didn't take it or it wasn't offered, then you just wouldn't ever touch on them.