"Also the sample size should be increased by a factor of 10."
You could say the same for just about any study. Obviously that would be a good thing. I don't know what the relevant p-values are, here, but my guess is that it's statistically significant. (I'm sure the full paper will include more statistical analysis of significance.)
I think more interesting would be to see how this varied across sector - these were all HR positions. It may be that the results would be quite different in, for example, programming positions.
In any case, it's an interesting question to be asking, and I'm glad people are doing research in it!
You've argued that if the the primes were basically random, we would expect Goldbach to hold, but as I understand it, we would expect to not be able to prove that it holds.
The fact that we can prove the ternary Goldbach conjecture is (necessarily) at least as surprising as it being true: in this case it seems to be significantly more surprising. Is the significance of this result in fact the techniques used, rather than the result itself?
Just as a quick note: I'm a counterexample to the assertion that anyone who needs a basic explanation of Fourier Series doesn't know enough maths to understand the primer.
I've got a strong (pure) mathematical background (degree in Maths & Philosophy from Oxford), and am now doing a PhD in CS, but my degree was entirely pure maths, and I never did any applied calculus. Admittedly, this isn't a common background, but one of the joys of writing on the internet is that you can write for whatever audience you choose!
Jeremy: thanks very much for providing these primers! For me, they've been great: there are lots of areas of maths which I've not looked at, and for a while I'd been wanting a good introduction to them which was at the right level for me: i.e. mathematically clear, without having to go into too much background, and these have been great at that.
I haven't used it for programming languages (though I intend to the next time I learn one), but I used it for my maths degree (for sit-down exam at the end of the year), and it seemed to be very effective. The danger is always that it can be time consuming to create the content for it.
Anki does look a bit raw, but worked absolutely fine for me (though transferring LaTeX-ed decks between devices was a hassle). There's also memrise.com, which mostly focuses on languages, but allows users to create content on any subject. It's also more easily shareable there, I think.
In any case, the science behind SRSs is good, and in my experience it helps a lot with memorisation!
You could say the same for just about any study. Obviously that would be a good thing. I don't know what the relevant p-values are, here, but my guess is that it's statistically significant. (I'm sure the full paper will include more statistical analysis of significance.)
I think more interesting would be to see how this varied across sector - these were all HR positions. It may be that the results would be quite different in, for example, programming positions.
In any case, it's an interesting question to be asking, and I'm glad people are doing research in it!