8 ms·
Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator
- throwanem 1y agoI love this! As a tool for helping folks with a good base in arithmetic develop statistical intuition, I can't think offhand of what I've seen that's better.
- croisillon 1y agoi like it and i skimmed the post but i don't understand why the default example 100 / 4~6 has a median of 20? there is no way of knowing why the range is between 4 and 6
- constantcrying 1y agoThe chance of 4~6 being less than 5 is 50%, the chance of it being greater is also 50%. The median of 100/4~6 has to be 100/5. >there is no way of knowing why the range is between 4 and 6 ??? There is. It is the ~ symbol.
- croisillon 1y agommh ok thanks, i guess i need extra maths training ;) i didn't mean knowing _that_ the range is between 4 and 6 but _why_, i thought the weighing would be explained by the reasoning, like: "we divide a €100 bill between possibly 4, rather 5 and most probably not 6 persons"
- constantcrying 1y ago>but _why_ Because that is how it is defined by the author of the article.
- perching_aix 1y agohow do you mean?
- rogueptr 1y agobrilliant work, polished ui. although sometimes give wrong ranges for equations like 100/1~(200~2000)
- thih9 1y agoCan you elaborate? What is the answer you’re getting and what answer would you expect?
- rogueptr 1y ago[dead]
- BrandoElFollito 1y agoHow do you process this equation ? 100 divided by something from one to ...?
- notfed 1y ago> 100 / 4~6 Means "100 divided by some number between 4 and 6"
- throwanem 1y ago"...some number with a 95% probability of falling between 4.0 and 6.0 inclusive," I believe.
- BrandoElFollito 1y agoYes, but this is not what op has. Their formula is 100 / 1~(20~200), with a double tilde
- djoldman 1y agoI perused the codebase but I'm unfamiliar with dart: https://github.com/filiph/unsure/blob/master/lib/src/calculation.dart https://github.com/filiph/unsure/blob/master/lib/src/calcula... I assume this is a montecarlo approach? (Not to start a flamewar, at least for us data scientists :) ).
- kccqzy 1y agoYes it is.
- porridgeraisin 1y agoCan you explain how? I'm an (aspiring)
- kccqzy 1y agoI didn't peruse the source code. I just read the linked article in its entirety and it says > The computation is quite slow. In order to stay as flexible as possible, I'm using the Monte Carlo method. Which means the calculator is running about 250K AST-based computations for every calculation you put forth. So therefore I conclude Monte Carlo is being used.
- constantcrying 1y agoLine 19 to 21 should be the Monte-Carlo sampling algorithm. The implementation is maybe a bit unintuitive but apparently he creates a function from the expression in the calculator, calling that function gives a random value from that function.
- hawthorns 1y agoIt's dead simple. Here is the simplified version that returns the quantiles for '100 / 2 ~ 4'. import numpy as np def monte_carlo(formula, iterations=100000): res = [formula() for _ in range(iterations)] return np.percentile(res, [0, 2.5, \*range(10, 100, 10), 97.5, 100]) def uncertain_division(): return 100 / np.random.uniform(2, 4) monte_carlo(uncertain_division, iterations=100000)
- timothylaurent 1y agoThis reminds me of https://www.getguesstimate.com/ https://www.getguesstimate.com/ , a probabilistic spreadsheet.
- Recursing 1y agoThe authors of Guesstimate are now working on https://www.squiggle-language.com/ https://www.squiggle-language.com/ Someone also turned it into the https://github.com/rethinkpriorities/squigglepy https://github.com/rethinkpriorities/squigglepy python library
- idkfasayer 1y ago[dead]
- filiph 1y agoWow, this is fantastic! I did not know about squiggle language, and it's basically what I was trying to get to from my unsure calculator through my next project (https://filiph.github.io/napkin/ https://filiph.github.io/napkin/). Squiggle looks and works much better. Thanks for the link!
- baq 1y agoI was looking for this. Seen it (or a similar tool) ages ago. Want to use it every 3 months or so to pretend that we know what we can squeeze in the roadmap for the quarter.
- deleted 1y ago[deleted]
- thih9 1y agoFeature request: allow specifying the probability distribution. E.g.: ‘~’: normal, ‘_’: uniform, etc.
- pyfon 1y agoNot having this feature is a feature—they mention this.
- thih9 1y agoNot really, or at least not permanently; uniform distribution is mentioned in a github changelog, perhaps it’s an upcoming feature: > 0.4.0 > BRAKING: x~y (read: range from x to y) now means "flat distribution from x to y". Every value between x and y is as likely to be emitted. > For normal distribution, you can now use x+-d, which puts the mean at x, and the 95% (2 sigma) bounds at distance d from x. https://github.com/filiph/unsure/blob/master/CHANGELOG.md#040 https://github.com/filiph/unsure/blob/master/CHANGELOG.md#04...
- tgv 1y agoI think they should be functions: G(50, 1) for a Gaussian with µ=50, σ=1; N(3) for a negative exponential with λ=3, U(0, 1) for a uniform distribution between 0 and 1, UI(1, 6) for an uniform integer distribution from 1 to 6, etc. Seems much more flexible, and easier to remember.
- rao-v 1y agoThis is terrific and it’s tempting to turn into a little python package. +1 for notation to say it’s ~20,2 to mean 18~22
- pvg 1y agoSmol Show HN thread a few years ago https://news.ycombinator.com/item?id=22630600 https://news.ycombinator.com/item?id=22630600
- kccqzy 1y agoI 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/d3fa7cdb064e03b16acfbefb76645744 https://gist.github.com/kccqzy/d3fa7cdb064e03b16acfbefb76645... Thank you filiph for this brilliant idea!
- deleted 1y ago[deleted]
- filiph 1y agoNice! Are you using your python script often? 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/ https://filiph.github.io/napkin/, anyway, but it's still a web app rather than a CLI tool.)
- kccqzy 1y agoYes. I have Python on my phone so I just run it.
- alexmolas 1y agois this the same as error propagation? I used to do a lot of that during my physics degree
- constantcrying 1y agoIt doesn't propagate uncertainty through the computation, but rather treats the expression as a single random variable.
- vessenes 1y agocool! are all ranges considered poisson distributions?
- re 1y agoNo: > Range is always a normal distribution, with the lower number being two standard deviations below the mean, and the upper number two standard deviations above. Nothing fancier is possible, in terms of input probability distributions.
- constantcrying 1y agoAn alternative approach is using fuzzy-numbers. If evaluated with interval arithmetic you can do very long calculations involving uncertain numbers very fast and with strong mathematical guarantees. It would especially outperform the Monte-Carlo approach drastically.
- sixo 1y agoThis assumes the inputs are uniform distributions, or perhaps normals depending on what exactly fuzzy numbers mean. M-C is not so limited.
- constantcrying 1y agoNo. It assumes the numbers aren't random at all. Although fuzzy-number can be used to model many different kinds of uncertainties.
- filiph 1y agoI'm familiar with fuzzy numbers (e.g. see my https://filiph.net/fuzzy/ https://filiph.net/fuzzy/ toy) but I didn't know there's arithmetic with fuzzy numbers. How is it done? Do you have a link?
- constantcrying 1y agoThere is a book by Hanss on it. It focuses on the sampling approach (he calls it "transformation method") though. If you want to do arithmetic and not a black box approach you just have to realize that you can perform them on the alpha-cuts with ordinary interval arithmetic. Then you can evaluate arbitrary expressions involving fuzzy numbers, keeping the strengths and weaknesses of interval arithmetic. The sampling based approach is very similar to Monte-Carlo, but you sample at certain well defined points.
- krick 1y agoIt sounds like a gimmick at first, but looks surprisingly useful. I'd surely install it if it was available as an app to use alongside my usual calculator, and while I cannot quite recall a situation when I needed it, it seems very plausible that I'll start finding use cases once I have it bound to some hotkey on my keyboard.
- deleted 1y ago[deleted]
- NunoSempere 1y ago> if it was available as an app Consider https://f-droid.org/en/packages/com.nunosempere.distributioncalculator/ https://f-droid.org/en/packages/com.nunosempere.distribution...
- hyperbolablabla 1y agoThey use dart as their primary language so it should be easy to make a flutter app from it...
- PennRobotics 1y agoI just threw numbers into there (population x ownership percent x replacement frequency x unit cost) to estimate the annual revenue of the smartphone market and got a few percentage points away from what the internet reports is the true value. Because there are trig functions, this would also be nice for reverse engineering of complex parts from simple measurements (feature volumes, corner angles, cross-sectional areas) Multimodal would be nice but not necessary. Inverse trig functions would be interesting but complicated and not necessary. In any case, this tool is more convenient than opening Python every time I want to estimate a range of answers.
- ttoinou 1y agoWould be nice to retransform the output into an interval / gaussian distribution 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 Drake Equation or equation multiplying probabilities can also be seen in log space, where the uncertainty is on the scale of each probability, and the final probability is the product of exponential of the log probabilities. And we wouldnt have this negative issue
- omoikane 1y agoIf I am reading this right, a range is expressed as a distance between the minimum and maximum values, and in the Monte Carlo part a number is generated from a uniform distribution within that range[1]. But if I just ask the calculator "1~2" (i.e. just a range without any operators), the histogram shows what looks like a normal distribution centered around 1.5[2]. Shouldn't the histogram be flat if the distribution is uniform? [1] https://github.com/filiph/unsure/blob/123712482b7053974cbef9ffa7ba46c1cdfb765f/lib/src/range.dart#L27 https://github.com/filiph/unsure/blob/123712482b7053974cbef9... [2] https://filiph.github.io/unsure/#f=1~2 https://filiph.github.io/unsure/#f=1~2
- hatthew 1y agoUnder the "Limitations" section: > Range is always a normal distribution, with the lower number being two standard deviations below the mean, and the upper number two standard deviations above. Nothing fancier is possible, in terms of input probability distributions.
- filiph 1y agoPart of the confusion here is likely that the tool, as seen on the web, probably lags significantly behind the code. I've started using a related but different tool (https://filiph.github.io/napkin/ https://filiph.github.io/napkin/). The HN mods gave me an opportunity to resubmit the link, so I did. If I had more time, I'd have also upgraded the tool to the latest version and fix the wording. But unfortunately, I didn't find the time to do this. Apologies for the confusion!
- marcodiego 1y agoI 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.
- NunoSempere 1y agoI'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.
- SamBam 1y agoI 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?
- pyfon 1y agoOnly 1 percent of values would end up being 100+ on a uniform distribution. For normal it is higher but maybe not much more so.
- lswainemoore 1y agoThat may be true, but if you look at the distribution it puts out for this, it definitely smells funny. It looks like a very steep normal distribution, centered at 0 (ish). Seems like it should have two peaks? But maybe those are just getting compressed into one because of resolution of buckets?
- 1y ago
- gregschlom 1y agoThe ASCII art (well technically ANSI art) histogram is neat. Cool hack to get something done quickly. I'd have spent 5x the time trying various chart libraries and giving up.
- Retr0id 1y agoOn a similar note, I like the crude hand-drawn illustrations a lot. Fits the "napkin" theme.
- smartmic 1y agoHere [1] is a nice implementation written in Awk. A bit rough around the edges, but could be easily extended. [1] https://github.com/stefanhengl/histogram https://github.com/stefanhengl/histogram
- NunoSempere 1y agoI have written similar tools - for command line, fermi: https://git.nunosempere.com/NunoSempere/fermi https://git.nunosempere.com/NunoSempere/fermi - for android, a distribution calculator: https://f-droid.org/en/packages/com.nunosempere.distributioncalculator/ https://f-droid.org/en/packages/com.nunosempere.distribution... People might also be interested in https://www.squiggle-language.com/ https://www.squiggle-language.com/, which is a more complex version (or possibly <https://git.nunosempere.com/personal/squiggle.c https://git.nunosempere.com/personal/squiggle.c>, which is a faster but much more verbose version in C)
- NunoSempere 1y agoFermi in particular has the following syntax ``` 5M 12M # number of people living in Chicago beta 1 200 # fraction of people that have a piano 30 180 # minutes it takes to tune a piano, including travel time / 48 52 # weeks a year that piano tuners work for / 5 6 # days a week in which piano tuners work / 6 8 # hours a day in which piano tuners work / 60 # minutes to an hour ``` multiplication is implied as the default operation, fits are lognormal.
- NunoSempere 1y agoHere is a thread with some fun fermi estimates made with that tool: e.g., number of calories NK gets from Russia: https://x.com/NunoSempere/status/1857135650404966456 https://x.com/NunoSempere/status/1857135650404966456 900K 1.5M # tonnes of rice per year NK gets from Russia * 1K # kg in a tone * 1.2K 1.4K # calories per kg of rice / 1.9K 2.5K # daily caloric intake / 25M 28M # population of NK / 365 # years of food this buys / 1% # as a percentage
- kqr 1y agoOh, this is very similar to what I have with Precel, less syntax. Thanks for sharing!
- antman 1y agoI tried the unsure calc and the android app and they seem to produce different results?
- alex-moon 1y ago> The UI is ugly, to say the least. I actually quite like it. Really clean, easy to see all the important elements. Lovely clear legible monospace serif font.
- roughly 1y agoI 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 large people keep their mental error bars too close. 2) probability is rarely truly uncorrelated - call this the “Mortgage Derivatives” maxim. In the family example, rent is very likely to be correlated with food costs - so, if rent is high, food costs are also likely to be high. This skews the distribution - modeling with an unweighted uniform distribution will lead to you being surprised at how improbable the actual outcome was. 3) In general normal distributions are rarer than people think - they tend to require some kind of constraining factor on the values to enforce. We see them a bunch in nature because there tends to be negative feedback loops all over the place, but once you leave the relatively tidy garden of Mother Nature for the chaos of human affairs, normal distributions get pretty abnormal. I like this as a tool, and I like the implementation, I’ve just seen a lot of people pick up statistics for the first time and lose a finger.
- youainti 1y ago> I’ve just seen a lot of people pick up statistics for the first time and lose a finger. I love this. I've never though of statistics like a power tool or firearm, but the analogy fits really well.
- ninalanyon 1y agoUnfortunately it's usually someone else who loses a finger, not the person wielding the statistics.
- btilly 1y agoI 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/ https://blog.codinghorror.com/how-good-an-estimator-are-you/.
- chris_wot 1y agoThere's an amazing scene in "This is Spinal Tap" where Nigel Tufnel had been brainstorming a scene where Stonehenge would be lowered from above onto the stage during their performance, and he does some back of the envelope calculations which he gives to the set designer. Unfortunately, he mixes the symbol for feet with the symbol for inches. Leading to the following: https://www.youtube.com/watch?v=Pyh1Va_mYWI https://www.youtube.com/watch?v=Pyh1Va_mYWI
- vortico 1y agoCool! Some random requests to consider: Could the range x~y be uniform instead of 2 std dev normal (95.4%ile)? Sometimes the range of quantities is known. 95%ile is probably fine as a default though. Also, could a symbolic JS package be used instead of Monte-Carlo? This would improve speed and precision, especially for many variables (high dimensions). Could the result be shown in a line plot instead of ASCII bar chart?
- OisinMoran 1y agoThis is neat! If you enjoy the write up, you might be interested in the paper “Dissolving the Fermi Paradox” which goes even more on-depth into actually multiplying the probability density functions instead of the common point estimates. It has the somewhat surprising result that we may just be alone. https://arxiv.org/abs/1806.02404 https://arxiv.org/abs/1806.02404
- nritchie 1y agoHere (https://uncertainty.nist.gov/ 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.
- filiph 1y agoI think I was looking at this and several other similar calculators when creating the linked tool. This is what I mean when I say "you'll want to use something more sophisticated". 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).
- ashu1461 1y agoSo is it 250k calculations for every approximation window ? So i guess it will only be able to calculate upto 3-4 approximations comfortably ? Any reason why we kept it 250k and now a lower number like 10k
- Aachen 1y agohttps://qalculate.github.io 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?
- filiph 1y agoIt's all computed in the browser so yeah, it's JavaScript. Still, 8 seconds is a lot -- I was targeting sub-second computation times (which I find alright).
- internetter 1y agoYes! (5±6)*(9±12) => 45±81. Uncertainty propagation!
- explosion-s 1y agoI made one that's much faster because it instead modifies the normal distribution instead of sending thousands of samples: https://gistpreview.github.io/?757869a716cfa1560d6ea0286ee1b56b https://gistpreview.github.io/?757869a716cfa1560d6ea0286ee1b...
- etbebl 1y agoThis is more limited. I just tested and for one example, exponentiation seems not to be supported.
- lorenzowood 1y agoSee also Guesstimate https://getguesstimate.com 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.
- montag 1y agoThank you, I would have mentioned this myself, but forgot the name of it.
- BOOSTERHIDROGEN 1y agoawesome
- kqr 1y agoI have made a similar tool but for the command line[1] with similar but slightly more ambitious motivation[2]. I really like that more people are thinking in these terms. Reasoning about sources of variation is a capability not all people are trained in or develop, but it is increasingly important.[3] [1]: https://git.sr.ht/~kqr/precel https://git.sr.ht/~kqr/precel [2]: https://entropicthoughts.com/precel-like-excel-for-uncertain-values https://entropicthoughts.com/precel-like-excel-for-uncertain... [3]: https://entropicthoughts.com/statistical-literacy https://entropicthoughts.com/statistical-literacy
- nkron 1y agoReally cool! On iOS there's a noticeable delay when clicking the buttons and clicking the backspace button quickly zooms the page so it's very hard to use. Would love it in mobile friendly form!
- your_challenger 1y agoVery cool. This can also be used for LLM cost estimation. Basically any cost estimation I suppose. I use cloudflare workers a lot and have a few workers running for a variable amount of time. This could be useful to calculate a ball park figure of my infra cost. Thank you!
- danpalmer 1y agoThis is awesome. I used Causal years ago to do something similar, with perhaps slightly more complex modelling, and it was great. Unfortunately the product was targeted at high paying enterprise customers and seems to have pivoted into finance now, I've been looking for something similar ever since. This probably solves at least, err... 40~60% of my needs ;)
- chacha21 1y agoChalk also supports uncertainty : https://chachatelier.fr/chalk/chalk-features.php https://chachatelier.fr/chalk/chalk-features.php (combined with arbitrary long numbers and interval arithmetic)
- NotAnOtter 1y agoThis is super cool. It seems to break for ranges including 0 though 100 / -1~1 = -3550~3500 I think the most correct answer here is -inf~inf
- filiph 1y agoI'd argue this is WAI. It's hard for me to imagine _dividing_ by -1~1 in a real-world scenario, but let's say we divide by 0~10, which also includes zero. For example, we are dividing the income between 0 to 10 shareholders (still forced, but ok). Clearly, it's possible to have a division by zero here, so "0 sharehodlers would each get infinity". And in fact, if you try to compute 500 / 0, or even 500~1000 / 0, it will correctly show infinity. But if you divide by a range that merely _includes_ zero, I don't think it should give you infinity. Ask yourself this: does 95% of results of 500 / 0~10 become infinity?
- laalshaitaan 1y agolove it! gonna use this instead of calculating my own extremes now
- usgroup 1y agoInterval/affine arithmetic are alternatives which do not make use of probabilities for this these kinds of calculations. https://en.wikipedia.org/wiki/Interval_arithmetic https://en.wikipedia.org/wiki/Interval_arithmetic I think arbitrary distribution choice is dangerous. You're bound to end up using lots of quantities that are integers, or positive only (for example). "Confidence" will be very difficult to interpret. Does it support constraints on solutions? E.g. A = 3~10, B = 4 - A, B > 0
- po1nt 1y agoI love it! Now I need it in every calculator
- dmos62 1y agoLove it! I too have been toying with reasoning about uncertainty. I took a much less creative approach though and just ran a bunch of geometric brownian motion simulations for my personal finances [0]. My approach has some similarity to yours, though much less general. It displays the (un)certainty over time (using percentile curves), which was my main interest. Also, man, the UI, presentation, explanations: you did a great job, pretty inspiring. [0] https://dmos62.github.io/personal-financial-growth-simulator/ https://dmos62.github.io/personal-financial-growth-simulator...
- 97-109-107 1y agoThe histogram is great, nice work; I want to ask about adjacent projects - user interface libraries that provide input elements for providing ranges and approximate values. I'm starting my search around https://www.inkandswitch.com/ https://www.inkandswitch.com/ and https://malleable.systems/catalog/ https://malleable.systems/catalog/ but I think our collective memory has seen more examples.
- usgroup 1y agoI think the SWI Prolog clpBNR package is the most complete interval arithmetic system. It also supports arbitrary constraints. https://github.com/ridgeworks/clpBNR https://github.com/ridgeworks/clpBNR
- elia_42 1y agoInteresting. I like the notation and the histogram that comes out with the output. I also like the practical examples you gave (e.g. the application of the calculator to business and marketing cases). I will try it out with simple estimates in my marketing campaigns.
- cluckindan 1y ago”Without further knowledge, the calculator cannot know that a negative number is impossible (in other words, you can't have -5 civilizations, for example).” Not true. If there are no negative terms, the equation cannot have negative values.
- kqr 1y agoThe calculator cannot know whether there are no negative terms. For example, if people's net worth is distributed 0.2–400, there's likely a significant chunk of people who are, on the whole, in debt. These will be represented as a negative term, even though their distribution was characterised by positive numbers.
- deleted 1y ago[deleted]
- burning_hamster 1y agoThe range notation indicates 95% confidence intervals, not the minima and maxima. If the lower bounds are close enough to zero (and the interval is large enough), then there may some residual probability mass associated with negative values of the variable.
- ralferoo 1y agoOn 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 was "1.5~3 x 0.9~1.0 x 0.1~0.4 x 0.1~1.0 x 0.1~1.0 x 0.1~0.2 x 304~10000" - every single range was positive, so regardless of what this represents, it should be impossible to get a negative result. I guess this is a consequence of "I am not sure about the exact number here, but I am 95% sure it's somewhere in this range" so it's actually considering values outside of the specified range. In this case, 10% either side of all the ranges is positive except the large "304~10000". Trying with a simpler example: "1~2 x 1~2" produces "1.3~3.4" as a result, even though "1~4" seems more intuitive. I assume this is because the confidence of 1 or 4 is now only 90% if 1~2 was at 95%, but it still feels off. I wonder if the 95% thing actually makes sense, but I'm not especially good at stats, certainly not enough to be sure how viable this kind of calculator is with a tighter range. But just personally, I'd expect "1~2" to mean "I'm obviously not 100% sure, or else I wouldn't be using this calculator, but for this experiment assume that the range is definitely within 1~2, I just don't know where exactly".
- kqr 1y agoThe calculator in Emacs has support for what it is you request, which it calls "interval forms". Interval form arithmetic simply means executing the operations in parallel on both ends of the interval. It also has support for "error forms" which is close to what the calculator in OP uses. That takes a little more sophistication than just performing operations on the lower and upper number in parallel. In particular, the given points don't represent actual endpoints on a distribution, but rather low and high probability events. Things more or less likely than those can happen, it's just rare. > I'm not especially good at stats It shows! All the things you complain about make perfect sense given a little more background knowledge.
- OisinMoran 1y agoIs it actually just doing it at both ends or something nore complex? Because for example if I did 7 - (-1~2)^2 the actual range would be 3-7 but just doing both ends of the interval would give 3-6 as the function is maximised inside the range.
- ThouYS 1y agosimilar to guesstimate, which does the same but for spreadsheets: https://www.getguesstimate.com/ https://www.getguesstimate.com/
- dejongh 1y agoCool. It would be great to extend with a confidence operator. Something like: Without default confidence: 0~9 With confidence: 0%100~9%95 We are sure it is 0 or more and we are %95 certain it is 9 or less. Would that work?
- thomascountz 1y agoThis reminded me of this submission a few days ago: Napkin Math Tool[1]. [1]: https://news.ycombinator.com/item?id=43389455 https://news.ycombinator.com/item?id=43389455
- godDLL 1y agoSo is it like plugging in a normal distribution into some arithmetic? 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.
- constantcrying 1y agoNo. It is sampling the resulting distribution with Monte-Carlo.
- henryaj 1y agoAlso very very good is Guesstimate - https://www.getguesstimate.com/ https://www.getguesstimate.com/.
- trieloff 1y agohttps://www.getguesstimate.com/ https://www.getguesstimate.com/ is this, as a spreadsheet
- spzzz 1y agoThis is really useful, but is this correct? persons = 10~15 // → 10~15 budget = persons * 1~2 // → 12~27 Should it not say 10-30?
- wongarsu 1y agoIf they are truly independent of each other some of the uncertainty cancels out. 10 people and a budget of $1/person are both unlikely events, and two unlikely events occurring independently of each other is even more unlikely. And because the calculator is not about the full range of possible values but about the values in the 95% confidence interval this leads to the outer edges of the range now falling outside the 95% confidence interval
- peeters 1y agoIs there a way to do non-scalar multiplication? E.g if I want to say "what is the sum of three dice rolls" (ignoring the fact that that's not a normal distro) I want to do 1~6 * 3 = 1~6 + 1~6 + 1~6 = 6~15. But instead it does 1~6 * 3 = 3~18. It makes it really difficult to do something like "how long will it take to complete 1000 tasks that each take 10-100 days?"
- didou9 1y ago[dead]
- frugalmail 1y agoGreat implementation. I would love to see this syntax added to spreadsheet software. Far less complicated than current functions.
- bionhoward 1y agoYooo I already installed this on my Home Screen and used it like 20 times, great job, it’s so simple and genius!