I don't understand why this is relevant.
Hm. When I read the great-grandparent earlier, I got the impression it would be helpful to corroborate this claim in the great-great-grandparent:
In any population other than the one for which the test has been normed to follow a normal distribution with mean of 100 and standard deviation of 15, yes, results need not be normally distributed or to have a standard deviation of 15.
Rereading the great-grandparent now, it's not clear to me why I got that impression. (I may have been thinking that the "general population," as it contains distinct subpopulations, will be at best a mixture Gaussian rather than a Gaussian.)
I do agree that private_messaging's claim- that the ratio we see at the tails doesn't seem to follow what would be predicted by the normal distribution- hinges on the right tail being fatter than what the normal distribution predicts. (The mixture Gaussian claim is irrelevant if you've split the general population up into subpopulations that are normally distributed, unless the low IQ group contains subpopulations, so it isn't normally distributed. There's some reason to believe this is true for African Americans, for example, if you don't separate out people by ancestry and recency of immigration.)
The data is sparse enough that I would not be surprised if this were the case, but I don't think anyone's directly investigated it, and a few of the investigations that hinge on the thickness of the tails (like Sex Differences in Mathematical Aptitude, which predicts female representation in elite math institutions by looking at the mean and variance of math SAT scores of large populations) seem to have worked well, which is evidence for normality.
I've been wondering how useful it is for the typical academically strong high schooler to learn math deeply. Here by "learn deeply" I mean "understanding the concepts and their interrelations" as opposed to learning narrow technical procedures exclusively.
My experience learning math deeply
When I started high school, I wasn't interested in math and I wasn't good at my math coursework. I even got a D in high school geometry, and had to repeat a semester of math.
I subsequently became interested in chemistry, and I thought that I might become a chemist, and so figured that I should learn math better. During my junior year of high school, I supplemented the classes that I was taking by studying calculus on my own, and auditing a course on analytic geometry. I also took physics concurrently.
Through my studies, I started seeing the same concepts over and over again in different contexts, and I became versatile with them, capable of fluently applying them in conjunction with one another. This awakened a new sense of awareness in me, of the type that Bill Thurston described in his essay Mathematics Education:
I understood the physical world, the human world, and myself in a way that I had never before. Reality seemed full of limitless possibilities. Those months were the happiest of my life to date.
More prosaically, my academic performance improved a lot, and I found it much easier to understand technical content (physics, economics, statistics etc.) ever after.
So in my own case, learning math deeply had very high returns.
How generalizable is this?
I have an intuition that many other people would benefit a great deal from learning math deeply, but I know that I'm unusual, and I'm aware of the human tendency to implicitly assume that others are similar to us. So I would like to test my beliefs by soliciting feedback from others.
Some ways in which learning math deeply can help are:
Some arguments against learning math deeply being useful are:
I'd be grateful to anyone who's able to expand on these three considerations, or who offers additional considerations against the utility of learning math deeply. I would also be interested in any anecdotal evidence about benefits (or lack thereof) that readers have received from learning math deeply.