I looked at your post and bounced off the first time. To give a concrete reason, there were a few terms I wasn’t familiar with (e.g. L-Theanine, CBD Oil, L-Phenylalanine, Bupropion, THC oil), but I think it was overall some “there’s an inferential distance here which makes the post heavy for me”. What also made the post heavy was that there were lots of markets—which I understand makes conceptual sense, but makes it heavy nevertheless.
I did later come back to the post and did trade on most of the markets, as I am a big fan of prediction markets and also appreciate people doing self-experiments. I wouldn’t have normally done that, as I don’t think I know basically anything about what to expect there—e.g. my understanding of Cohen’s d is just “it’s effect size, 1 d basically meaning one standard deviation”, and I haven’t even played with real numerical examples.
(I have had this “this assumes a bit too much statistics for me / is heavy”problem when quickly looking at your self-experiment posts. And I do have a mathematical background, though not from statistics.)
I’d guess that you believe that the statistics part is really important, and I don’t disagree with that. For exposition I think it would still be better to start with something lighter. And if one could have a reasonable prediction market on something more understandable (to laypeople), I’d guess that would result in more attention and still possibly useful information. (It is unfortunate that attention is very dependent on the “attractiveness” of the market instead of “quality of operationalization”.)
I guess I should’ve just said “effect size”, and clarify in a footnote that I mean Cohen’s d.
And if the nootropics post was too statistics-heavy for someone with a math background, I probably need to tone it down/move it to an appendix. I think I can have quality of operationalization if I’m willing to be sloppy in the general presentation (as people probably don’t care as much whether I use Cohen’s d or Hedge’s g or whatever).
I looked at your post and bounced off the first time. To give a concrete reason, there were a few terms I wasn’t familiar with (e.g. L-Theanine, CBD Oil, L-Phenylalanine, Bupropion, THC oil), but I think it was overall some “there’s an inferential distance here which makes the post heavy for me”. What also made the post heavy was that there were lots of markets—which I understand makes conceptual sense, but makes it heavy nevertheless.
I did later come back to the post and did trade on most of the markets, as I am a big fan of prediction markets and also appreciate people doing self-experiments. I wouldn’t have normally done that, as I don’t think I know basically anything about what to expect there—e.g. my understanding of Cohen’s d is just “it’s effect size, 1 d basically meaning one standard deviation”, and I haven’t even played with real numerical examples.
(I have had this “this assumes a bit too much statistics for me / is heavy”problem when quickly looking at your self-experiment posts. And I do have a mathematical background, though not from statistics.)
I’d guess that you believe that the statistics part is really important, and I don’t disagree with that. For exposition I think it would still be better to start with something lighter. And if one could have a reasonable prediction market on something more understandable (to laypeople), I’d guess that would result in more attention and still possibly useful information. (It is unfortunate that attention is very dependent on the “attractiveness” of the market instead of “quality of operationalization”.)
Thank you so much for trading on the markets!
I guess I should’ve just said “effect size”, and clarify in a footnote that I mean Cohen’s d.
And if the nootropics post was too statistics-heavy for someone with a math background, I probably need to tone it down/move it to an appendix. I think I can have quality of operationalization if I’m willing to be sloppy in the general presentation (as people probably don’t care as much whether I use Cohen’s d or Hedge’s g or whatever).