> Maybe there’s a story to be told about a young person finding uncertainty uncomfortable,

Us data oriented STEM loving types love being right, right? So I find it weird that this makes many of us dislike statistics. I find this especially considering how many people love to talk about quantum mechanics. But I think one of the issues here is that people have the wrong view of statistics and misunderstand what probability is really about. OP is exactly right, it is about uncertainty.

So if we're concerned with being right, you have to use probability and statistics. In your physics and/or engineering classes you probably had a teacher or TA who was really picky with things like sigfigs[0] or including your errors/uncertainty (like ±). The reason is because these subtle details are actually incredibly powerful. I'm biased because I came over from physics and moved into CS, but I found these concepts translated quite naturally and were still very important over here. Everything we work with is discrete and much of it is approximating continuous functions. Probabilities give us this really powerful tool to be more right!

Think about any measurement you make. Go grab a ruler. Which is more accurate? Writing 10cm or 10cm ± 1cm? It's clearly the latter, right? But this isn't so different than writing something like U(9cm,11cm) or N(10cm,0.6cm). In fact, you'd be even more correct if you wrote down your answer distributionally![1] It gives us much more information!

So honestly I'd love to see a cultural shift in our nerd world. For more appreciation of probabilities and randomness. While motivated by being more right it opens the door to a lot of new and powerful ways of thinking. You have to constantly be guessing your confidence levels and challenging yourself. You no longer can read data as absolute and instead read it as existing with noise. You no longer take measurements with absolute confidence because you will be forced to understand that every measurement is a proxy for what you want to measure. These concepts are paradigm shifting in how one thinks about the world. They will help you be more right, they will help you solve greater challenges, and at the end of the day, when people are on the same page it makes it easier to communicate. Because it no longer is about being right or wrong, it is about being more or less right. You're always wrong to some degree, so it never really hurts when someone points out something you hadn't considered. There's no ego to protect, just updating your priors. Okay, maybe that last one is a little too far lol. But I absolutely love this space and I just want to share that with others. There's just a lot of mind opening stuff to be learned from this (and other) math field, especially as you get into metric theory. Even if you never run the numbers or write the equations, there are still really powerful lessons to learn that can be used in your day to day life. Math, at the end of the day, is about abstraction and representation. As programmers, I think we've all experienced how powerful these tools are.

[0] https://en.wikipedia.org/wiki/Significant_figures

[1] Technically 10cm ± 1cm is going to be Uniform(9cm,11cm) but realistically that variance isn't going to be uniformly distributed and much more likely to be normal-like. You definitely have a bias towards the actual mark, right?! (Usually we understand ± through context. I'm not trying to be super precise here and instead focusing on the big picture. Please dig in more if you're interested and please leave more nuance if you want to expand on this, but let's also make sure big picture is understood before we add complexity :)