I am sorry if I have straw manned you, and I think your above post is generally correct.
I think we are cumming from two different worlds.
You are coming from Metaculus where people make a lot of predictions. Where having 50+ predictions is the norm and the thus looking at a U(0, 1) gives a lot of intuitive evidence of calibration.
I come from a world where people want to improve in all kids of ways, and one of them is prediction, few people write more than 20 predictions down a year, and when they do they more or less ALWAYS make dichotomous predictions. I expect many of my readers to be terrible at predicting just like myself.
You are reading a post with the message “raise the sanity waterline from 2% to 5% of your level” and asking “why is this better than making 600 predictions and looking at their inverse CDF”, and the answer is: it’s not, but it’s still relevant because most people do not make 600 predictions and do not know what an inverse CDF is. I am even explaining what an normal distribution is because I do not expect my audience to know...
You are absolutely correct they probably do not share an error distribution. But I am trying to get people from knowing 1 distribution to knowing 2.
Scot Alexander makes a “when I predict this” then “it really means that”, every year for his binary predictions, This gives him an intuitive feel for “I should adjust my odds up/down by x”. I am trying to do the same for Normal Distribution predictions, so people can check their predictions.
I agree your methodology is superior :), All I propose that people sometimes make continuous predictions, and if they want to start doing that and track how much they suck, then I give them instructions to quickly getting a number for how well it is going.
If you’re making ~20 predictions a year, you shouldn’t be doing any funky math to analyse your forecasts. Just go through each one after the fact and decide whether or not the forecast was sensible with the benefit of hindsight.
I am even explaining what an normal distribution is because I do not expect my audience to know...
I think this is exactly my point, if someone doesn’t know what a normal distribution is, maybe they should be looking at their forecasts in a fuzzier way than trying to back fit some model to them.
All I propose that people sometimes make continuous predictions, and if they want to start doing that and track how much they suck, then I give them instructions to quickly getting a number for how well it is going.
I disagree that’s all you propose. As I said in an earlier comment, I’m broadly in favour of people making continuous forecasts as they convey more information. You paired your article with what I believe is broadly bad advise around analysing those forecasts. (Especially if we’re talking about a sample of ~20 forecasts)
I would love you as a reviewer of my second post as there I will try to justify why I think this approach is better, you can even super dislike it before I publish if you still feel like that when I present my strongest arguments, or maybe convince me that I am wrong so I dont publish part 2 and make a partial retraction for this post :). There is a decent chance you are right as you are the stronger predictor of the two of us :)
I am sorry if I have straw manned you, and I think your above post is generally correct. I think we are cumming from two different worlds.
You are coming from Metaculus where people make a lot of predictions. Where having 50+ predictions is the norm and the thus looking at a U(0, 1) gives a lot of intuitive evidence of calibration.
I come from a world where people want to improve in all kids of ways, and one of them is prediction, few people write more than 20 predictions down a year, and when they do they more or less ALWAYS make dichotomous predictions. I expect many of my readers to be terrible at predicting just like myself.
You are reading a post with the message “raise the sanity waterline from 2% to 5% of your level” and asking “why is this better than making 600 predictions and looking at their inverse CDF”, and the answer is: it’s not, but it’s still relevant because most people do not make 600 predictions and do not know what an inverse CDF is. I am even explaining what an normal distribution is because I do not expect my audience to know...
You are absolutely correct they probably do not share an error distribution. But I am trying to get people from knowing 1 distribution to knowing 2.
Scot Alexander makes a “when I predict this” then “it really means that”, every year for his binary predictions, This gives him an intuitive feel for “I should adjust my odds up/down by x”. I am trying to do the same for Normal Distribution predictions, so people can check their predictions.
I agree your methodology is superior :), All I propose that people sometimes make continuous predictions, and if they want to start doing that and track how much they suck, then I give them instructions to quickly getting a number for how well it is going.
I still think you’re missing my point.
If you’re making ~20 predictions a year, you shouldn’t be doing any funky math to analyse your forecasts. Just go through each one after the fact and decide whether or not the forecast was sensible with the benefit of hindsight.
I think this is exactly my point, if someone doesn’t know what a normal distribution is, maybe they should be looking at their forecasts in a fuzzier way than trying to back fit some model to them.
I disagree that’s all you propose. As I said in an earlier comment, I’m broadly in favour of people making continuous forecasts as they convey more information. You paired your article with what I believe is broadly bad advise around analysing those forecasts. (Especially if we’re talking about a sample of ~20 forecasts)
I would love you as a reviewer of my second post as there I will try to justify why I think this approach is better, you can even super dislike it before I publish if you still feel like that when I present my strongest arguments, or maybe convince me that I am wrong so I dont publish part 2 and make a partial retraction for this post :). There is a decent chance you are right as you are the stronger predictor of the two of us :)
I’d be happy to.
I upvoted all comments in this thread for constructive criticism, response to it, and in the end even agreeing to review each other!