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Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

filiph.github.io

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Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#61

Post by SamBam »

NunoSempere wrote: post #57
marcodiego wrote: post #37

I put "1 / (-1~1)" and expected something around - to + infinty. It instead gave me -35~35. I really don't known how good it is.

I'm guessing this is not an error. If you divide 1/normal(0,1), the full distribution would range from -inf to inf, but the 95% output doesn't have to.

I don't quite understand, probably because my math isn't good enough.

If you're treating -1~1 as a normal distribution, then it's centered on 0. If you're working out the answer using a Monte Carlo simulation, then you're going to be testing out different values from that distribution, right? And aren't you going to be more likely to test values closer to 0? So surely the most likely outputs should be far from 0, right?

When I look at the histogram it creates, it varies by run, but the most common output seems generally closest to zero (and sometimes is exactly zero). Wouldn't that mean that it's most frequently picking values closest to -1 or 1 denoninator?

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#63

Post by Aachen »

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 JavaScript, or is the server currently very busy?

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#64

Post by pyfon »

SamBam wrote: post #61
NunoSempere wrote: post #57

Earlier quoted context omitted.

I'm guessing this is not an error. If you divide 1/normal(0,1), the full distribution would range from -inf to inf, but the 95% output doesn't have to.

I don't quite understand, probably because my math isn't good enough. If you're treating -1~1 as a normal distribution, then it's centered on 0. If you're working out the answer using a Monte Carlo simulation, then you're going to be testing out different values from that distribution, right? And aren't you going to be more likely to test values closer to 0? So surely the most likely outputs should be far from 0, rig…

Only 1 percent of values would end up being 100+ on a uniform distribution.

For normal it is higher but maybe not much more so.

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#65

Post by Nevermark »

btilly wrote: post #52
roughly wrote: post #44

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…

I strongly agree with this, and particularly point 1. If you ask people to provide estimated ranges for answers that they are 90% confident in, people on average produce roughly 30% confidence intervals instead. Over 90% of people don't even get to 70% confidence intervals. You can test yourself at https://blog.codinghorror.com/how-good-an-estimator-are-you/ .

From link:

> Heaviest blue whale ever recorded

I don't think estimation errors regarding things outside of someone's area of familiarity say much.

You could ask a much "easier"" question from the same topic area and still get terrible answers: "What percentage of blue whales are blue?" Or just "Are blue whales blue?"

Estimating something often encountered but uncounted seems like a better test. Like how many cars pass in front of my house every day. I could apply arithmetic, soft logic and intuition to that. But that would be a difficult question to grade, given it has no universal answer.

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#67

Post by pertdist »

roughly wrote: post #44

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…

I did a project with non-technical stakeholders modeling likely completion dates for a big GANTT chart. Business stakeholders wanted probabilistic task completion times because some of the tasks were new and impractical to quantify with fixed times.

Stakeholders really liked specifying work times as t_i ~ PERT(min, mode, max) because it mimics their thinking and handles typical real-world asymmetrical distributions.

[Background: PERT is just a re-parameterized beta distribution that's more user-friendly and intuitive https://rpubs.com/Kraj86186/985700]

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#68

Post by notpushkin »

NunoSempere wrote: post #41

I have written similar tools - for command line, fermi: https://git.nunosempere.com/NunoSempere/fermi - for android, a distribution calculator: https://f-droid.org/en/packages/com.nunosempere.distribution... People might also be interested in https://www.squiggle-language.com/ , which is a more complex version (or possibly https://git.nunosempere.com/personal/squiggle.c >, which is a faster but much more verbose vers…

Would be a nice touch if Squiggle supported the `a~b` syntax :^)

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#69

Post by yen223 »

Nevermark wrote: post #65
btilly wrote: post #52

Earlier quoted context omitted.

I strongly agree with this, and particularly point 1. If you ask people to provide estimated ranges for answers that they are 90% confident in, people on average produce roughly 30% confidence intervals instead. Over 90% of people don't even get to 70% confidence intervals. You can test yourself at https://blog.codinghorror.com/how-good-an-estimator-are-you/ .

From link: > Heaviest blue whale ever recorded I don't think estimation errors regarding things outside of someone's area of familiarity say much. You could ask a much "easier"" question from the same topic area and still get terrible answers: "What percentage of blue whales are blue?" Or just "Are blue whales blue?" Estimating something often encountered but uncounted seems like a better test. Like how many cars pas…

I guess people didn't realise they are allowed to, and in fact are expected to, put very wide ranges for things they are not certain about.

Re: Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator

#70

Post by lorenzowood »

See also Guesstimate https://getguesstimate.com. Strengths include treating label and data as a unit, a space for examining the reasoning for a result, and the ability to replace an estimated distribution with sample data => you can build a model and then refine it over time. I'm amazed Excel and Google Sheets still haven't incorporated these things, years later.
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