All of DaveEtCircenses's Comments + Replies

A solution by method of "Thrash with linear regression, then get bored". I also make the (completely unsubstantiated) claim that an even split of students across houses will lead to better results.

Humblescrumble gets A,B,E,R and T.

Dragonslayer gets D,G,H,K and N.

Thought-Talon gets C,F,L*,M and Q*.

Serpentyne gets I*,J*,O,P and S*.

(Students marked * get a slightly better linear score in another House, but I balance the sizes)

I think the Law of Equal but Opposite Advice is extremely relevant here, in that there are two common failure modes for practicing.

The first of these is "not practicing what you actually do", and turbocharging helps with that.

The second of these is "practicing what you actually do, but inefficiently", and deliberate practice helps with that.

Of course, trying too hard to avoid the first failure mode yields the second (e.g. playing a whole piano piece through repeatedly), and trying too hard to avoid the second failure mode yields the first (e.g. memorising Anki flashcards for a language, but being unable to speak it since you didn't practice talking).

For your first half-question, "A Technical Explanation of Technical Explanation" [Edit: added link] sums up the big deal; Bayes Theorem is part of what actually underpins how to make a map reflect the territory (given infinite compute) - it is a necessary component. In comparison with other necessary components required to do this (i.e. logic, math, other basic probability) I would conjecture that Bayes is only special in that it is 'often' the last piece of the puzzle that is assembled in someone's mind, and thus takes on psychological significance. ... (read more)

1TAG
There are lots of ways of making the same point without bringing in Bayes.
3AVoropaev
I've skimmed over A Technical Explanation of Technical Explanation (you can make links end do over stuff by selecting the text you want to edit (as if you want to copy it); if your browser is compatible, toolbar should appear). I think that's the first time in my life when I've found out that I need to know more math to understand non-mathematical text. The text is not about Bayes' Theorem, but it is about application of probability theory to reasoning, which is relevant to my question. As far as I understand, Yudkowski writes about the same algorithm that Vladimir_Nesov describes in his answer to my question. Some nice properties of the algorithm are proved, but not very rigorously. I don't know how to fix it, which is not very surprising, since I know very little about statistics. In fact, I am now half-convinced to take a course or something like that. Thank you for that. As for the other part of your answer, it actually makes me even more confused. You are saying "using Bayes in life is more about understanding just how much priors matter than about actually crunching the numbers". To me it sounds similar to "using steel in life is more about understanding just how much whole can be greater than the sum of its parts than about actually making things from some metal". I mean, there is nothing inherently wrong with using a concept as a metaphor and/or inspiration. But it can sometimes cause miscommunication. And I am under impression that some people here (not only me) talk about Bayes' Theorem in a very literal sense.