111–120 of 170 posts
I like this! In the grand HN tradition of being triggered by a word in the post and going off on a not-quite-but-basically-totally-tangential rant: There’s (at least) three areas here that are footguns with these kinds of calculations: 1) 95% is usually a lot wider than people think - people take 95% as “I’m pretty sure it’s this,” whereas it’s really closer to “it’d be really surprising if it were not this” - by and…
Feature request: allow specifying the probability distribution. E.g.: ‘~’: normal, ‘_’: uniform, etc.
On the whole it seems like a nice idea, but there's a couple of weird things, such as: > Note: If you're curious why there is a negative number (-5) in the histogram, that's just an inevitable downside of the simplicity of the Unsure Calculator. Without further knowledge, the calculator cannot know that a negative number is impossible (in other words, you can't have -5 civilizations, for example). The input to this w…
They explain that the range you give as input is seen as only being 95% correct, so the calculator adds low-probability values outside of the ranges you specified.
I can see how that surprises you, but it's also a defensible design choice.
Consider maybe 1 + 1 ~ +-2 like Q factor, if you know what I mean.
That would help to filter out more probabilistic noise in using it to help reason with.
https://qalculate.github.io can do this also for as long as I've used it (only a couple years to be fair). I've got it on my phone, my laptop, even my server with apt install qalc. Super convenient, supports everything from unit conversion to uncertainty tracking The histogram is neat, I don't think qalc has that. On the other hand, it took 8 seconds to calculate the default (exceedingly trivial) example. Is that Jav…
Here ( https://uncertainty.nist.gov/ ) is another similar Monte Carlo-style calculator designed by the statisticians at NIST. It is intended for propagating uncertainties in measurements and can handle various different assumed input distributions.
The problem with similar tools is that of the very high barrier to entry. This is what my project was trying to address, though imperfectly (the user still needs to understand, at the very least, the concept of probability distributions).
I actually stumbled upon this a while ago from social media and the web version has a somewhat annoying latency, so I wrote my own version in Python. It uses numpy so it's faster. https://gist.github.com/kccqzy/d3fa7cdb064e03b16acfbefb76645... Thank you filiph for this brilliant idea!
The reason I'm asking: unsure also has a CLI version (which is leaps and bounds faster and in some ways easier to use) but I rarely find myself using it. (Nowadays, I use https://filiph.github.io/napkin/, anyway, but it's still a web app rather than a CLI tool.)