dynomight

Homepage: https://dynomight.net

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Observations about writing and commenting on the internet

I might not have described the original debate very clearly. My claim was that if Monty chose "leftmost non-car door" you still get the car 2/3 of the time by always switching and 1/3 by never switching. Your conditional probabilities look correct to me. The only thing you might be "missing" is that (A) occurs 2/3 of the time and (B) occurs only 1/3 of the time. So if you always switch your chance of getting the car is still (chance of A)*(prob of car given A) + (chance of B)*(prob of car given B)=(2/3)*(1/2) + (1/3)*(1) = (2/3).

One difference (outside the bounds of the original debate) is that if Monty behaves this way there are *other* strategies that also give you the car 2/3 of the time. For example, you could switch only in scenario B and not in scenario A. There doesn't appear to be any way to exploit Monty's behavior and do better than 2/3 though.

Observations about writing and commenting on the internet

Just to be clear, when talking about how people behave in forums, I mean more "general purpose" places like Reddit. In particular, I was not thinking about Less Wrong where in my experience, people have always bent over backwards to be reasonable!

Writing On The Pareto Frontier

I have two thoughts related to this:

First, there's a dual problem: Given a piece of writing that's along the Pareto frontier, how do you make it easy for readers who might have a utility function aligned with the piece to find it.

Related to this, for many people and many pieces of writing, a large part of the utility they get is from comments. I think this leads to dynamics where a piece where the writing that's less optimal can get popular and then get to a point on the frontier that's hard to beat.

johnswentworth's Shortform

I loved this book. The most surprising thing to me was the answer that people who were there in the heyday give when asked what made Bell Labs so successful: They always say it was the *problem*, i.e. having an entire organization oriented towards the goal of "make communication reliable and practical between any two places on earth". When Shannon left the Labs for MIT, people who were there immediately predicted he wouldn't do anything of the same significance because he'd lose that "compass". Shannon was obviously a genius, and he did much more after than most people ever accomplish, but still nothing as significant as what he did when at at the Labs.

How To Write Quickly While Maintaining Epistemic Rigor

I thought this was fantastic, very thought-provoking. One possibly easy thing that I think would be great would be links to a few posts that you think have used this strategy with success.

Factors of mental and physical abilities - a statistical analysis

Thanks, I clarified the noise issue. Regarding factor analysis, could you check if I understand everything correctly? Here's what I think is the situation:

We can write a factor analysis model (with a single factor) as

where:

- is observed data
- is a random latent variable
- is some vector (a parameter)
- is a random noise variable
- is the covariance of the noise (a parameter)

It always holds (assuming and are independent) that

In the simplest variant of factor analysis (in the current post) we use in which case you get that

You can check if this model fits by (1) checking that is Normal and (2) checking if the covariance of x can be decomposed as in the above equation. (Which is equivalent to having all singular values the same except one).

The next slightly-less-simple variant of factor analysis (which I think you're suggesting) would be to use where is a vector, in which case you get that

You can again check if this model fits by (1) checking that is Normal and (2) checking if the covariance of can be decomposed as in the above equation. (The difference is, now this doesn't reduce to some simple singular value condition.)

Do I have all that right?

Factors of mental and physical abilities - a statistical analysis

Thanks for pointing out those papers, which I agree can get at issues that simple correlations can't. Still, to avoid scope-creep, I've taken the less courageous approach of (1) mentioning that the "breadth" of the effects of genes is an active research topic and (2) editing the original paragraph you linked to to be more modest, talking about "does the above data imply" rather than "is it true that". (I'd rather avoid directly addressing 3 and 4 since I think that doing those claims justice would require more work than I can put in here.) Anyway, thanks again for your comments, it's useful for me to think of this spectrum of different "notions of g".

Factors of mental and physical abilities - a statistical analysis

Thanks, very clear! I guess the position I want to take is just that the data in the post gives reasonable evidence for **g** being *at least* the convenient summary statistic in 2 (and doesn't preclude 3 or 4).

What I was really trying to get at in the original quote is that some people seem to consider *this* to be the canonical position on **g**:

- Factor analysis provides rigorous statistical proof that there is some single underlying event that produces all the correlations between mental tests.

There are lots of articles that (while not explicitly stating the above position) refute it at length, and get passed around as proof that g is a myth. It's certainly true that position 5 is false (in multiple ways), but I just wanted to say that this doesn't mean anything for the evidence we have for 2.

If you're worried about computational complexity, that's OK. It's not something that I mentioned because (surprisingly enough...) this isn't something that any of the doctors discussed. If you like, let's call that a "valid cost" just like the medical risks and financial/time costs of doing tests. The central issue is if it's valid to worry about information causing harmful

downstream medical decisions.