Comment on Open thread, 11-17 August 2014

Wed, 13 Aug 2014 15:19:45 GMT

This seems like a good place to ask about something that I'm intensely curious about but haven't yet seen discussed formally. I've wanted to ask about it before, but I figured it's probably an obvious and well-discussed subject that I just haven't gotten to yet. (I only know the very basics of Bayesian thinking, I haven't read more than about 1/5 of the sequences so far, and I don't yet know calculus or advanced math of any type. So there are an awful lot of well-discussed LW-type subjects that I haven't gotten to yet.)

I've long conceived of Bayesian belief statements in the following (somewhat fuzzily conceived) way: Imagine a graph where the x-axis represents our probability estimate for a given statement being true and the y-axis represents our certainty that our probability estimate is correct. So if, for example, we estimate a probability of .6 for a given statement to be true but we're only mildly certain of that estimate, then our belief graph would probably look like a shallow bell curve centered on the .6 mark of the x-axis. If we were much more certain of our estimate then the bell curve would be much steeper.

I usually think of the height of the curve at any given point as representing how likely I think it is that I'll discover evidence that will change my belief. So for a low bell curve centered on .6, I think of that as meaning that I'd currently assign the belief a probability of around .6 but I also consider it likely that I'll discover evidence (if I look for it) that can change my opinion significantly in any direction.

I've found this way of thinking to be quite useful. Is this a well-known concept? What is it called and where can I find out more about it? Or is there something wrong with it?

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