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Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

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Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#51

Post by ozgooen »

evanb wrote: post #48

I was watching "Total time spent watching this video" video, and had a basic question. How does one tell guesstimate that there's a hard lower bound on a quantity. ie. Video Length is at least 0, because negative watch times are unphysical? I know the specified distribution in this case is very narrow (the video lasting between -1 and 0 minutes has probability ~0.000032). But the answer does come out to be 26±32, whi…

Good catch!

Right now the main distribution types are normal and uniform. In the video, I showed normal distributions, which have long tails in both directions.

In this case, a normal distribution isn't really correct, because, as you noted, being less than 0 is exceedingly unlikely.

I believe the correct way to deal with this is to use a lognormal distribution or something that has 0 chance of being less than 0. I don't yet have a simple way of doing this, but it's definitely on the agenda.

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#52

Post by evanb »

ozgooen wrote: post #51
evanb wrote: post #48

I was watching "Total time spent watching this video" video, and had a basic question. How does one tell guesstimate that there's a hard lower bound on a quantity. ie. Video Length is at least 0, because negative watch times are unphysical? I know the specified distribution in this case is very narrow (the video lasting between -1 and 0 minutes has probability ~0.000032). But the answer does come out to be 26±32, whi…

Good catch! Right now the main distribution types are normal and uniform. In the video, I showed normal distributions, which have long tails in both directions. In this case, a normal distribution isn't really correct, because, as you noted, being less than 0 is exceedingly unlikely. I believe the correct way to deal with this is to use a lognormal distribution or something that has 0 chance of being less than 0. I d…

You should be careful about committing too much to particular distributions being the "right" ones. For example, what if I know some variable is an odd integer between 1 and 11 inclusive with no support on any other real number?

Just something to keep in mind when abstracting what a distribution is.

edit: though as a short-hand for entry, Gaussian is usually a pretty good guess. Is there support for µ±σ instead of [low,high] in the works? Or support for numerical distributions?

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#54

Post by evanb »

ozgooen wrote: post #51
evanb wrote: post #48

I was watching "Total time spent watching this video" video, and had a basic question. How does one tell guesstimate that there's a hard lower bound on a quantity. ie. Video Length is at least 0, because negative watch times are unphysical? I know the specified distribution in this case is very narrow (the video lasting between -1 and 0 minutes has probability ~0.000032). But the answer does come out to be 26±32, whi…

Good catch! Right now the main distribution types are normal and uniform. In the video, I showed normal distributions, which have long tails in both directions. In this case, a normal distribution isn't really correct, because, as you noted, being less than 0 is exceedingly unlikely. I believe the correct way to deal with this is to use a lognormal distribution or something that has 0 chance of being less than 0. I d…

I should add that the negative portion of the answer may not be from sampling the small tail of the Video Length distribution, but is much more likely to be an artifact of how you calculate uncertainty. It might be better to find the median and go out some % in each direction asymmetrically. You can see that the Total Time is roughly flat and then peters out.

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#55

Post by ozgooen »

vive-la-liberte wrote: post #41
ozgooen wrote: post #37

Earlier quoted context omitted.

No. It needs to be online at this point.

Thanks for the prompt reply. Are you planning to open source all of it in the future or will it remain SaaS?

Right now the vast majority of it is open source. There is a component that is not: the rails server, but that's pretty tiny. The client can be developed on without that. If there's some interest I'm happy to make what's existing available.

I can't make guarantees about the distant future. There's a ton of work I would love to see happen with Guesstimate, and my guess is that much of it would only be possible if it becomes a company. This can still mean that it can be mostly open source, but I really have little idea what the situation would be at that time.

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#56

Post by evanb »

evanb wrote: post #54
ozgooen wrote: post #51

Earlier quoted context omitted.

Good catch! Right now the main distribution types are normal and uniform. In the video, I showed normal distributions, which have long tails in both directions. In this case, a normal distribution isn't really correct, because, as you noted, being less than 0 is exceedingly unlikely. I believe the correct way to deal with this is to use a lognormal distribution or something that has 0 chance of being less than 0. I d…

I should add that the negative portion of the answer may not be from sampling the small tail of the Video Length distribution, but is much more likely to be an artifact of how you calculate uncertainty. It might be better to find the median and go out some % in each direction asymmetrically. You can see that the Total Time is roughly flat and then peters out.

Actually, the negative portion could be from sampling the much more substantial negative tail of the Viewers distribution. Either way, constraints seem to be important!

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#57

Post by ozgooen »

evanb wrote: post #52
ozgooen wrote: post #51

Earlier quoted context omitted.

Good catch! Right now the main distribution types are normal and uniform. In the video, I showed normal distributions, which have long tails in both directions. In this case, a normal distribution isn't really correct, because, as you noted, being less than 0 is exceedingly unlikely. I believe the correct way to deal with this is to use a lognormal distribution or something that has 0 chance of being less than 0. I d…

You should be careful about committing too much to particular distributions being the "right" ones. For example, what if I know some variable is an odd integer between 1 and 11 inclusive with no support on any other real number? Just something to keep in mind when abstracting what a distribution is. edit: though as a short-hand for entry, Gaussian is usually a pretty good guess. Is there support for µ±σ instead of [l…

"Is there support for µ±σ instead of [low,high] in the works? " - There used to be. I'll be considering ways of adding it back.

"Or support for numerical distributions?" - By numerical distributions do you mean discreet distributions: like, a 40% of being '8' and a 60% chance of being '6'? If so, the answer is no. However, if you use the ternary operator it is possible to do very simple versions of this now. We do support totally random picks of different numbers though, using the pickRandom([3,5,3]) function. http://mathjs.org/docs/reference/functions/pickRandom.html

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#58

Post by ozgooen »

joshuahhh wrote: post #50
ozgooen wrote: post #18

Earlier quoted context omitted.

Definitely, keeping a close eye. Have long been interested in prediction markets. It would be nice to tie data from them and the Good Judgement project into tools like Guesstimate so people could make forecasts using other strong forecasts.

Pulling data from prediction markets into Guesstimate is an exciting idea. A few thoughts: * Prediction markets are usually for binary outcomes. I imagine the most useful role of binary variables in Guesstimate would be to mix two different distributions. "If Clinton wins, student debt in 2018 will look like distribution A; if Sanders wins, student debt in 2018 will look like distribution B". * I'm not sure how Augur…

That makes sense. It would be very useful to see estimates of how well Presidential candidates would do if they got elected.

In the future, one idea would be to keep track of people's metric estimates in Guesstimate, and later score and rank them on how well they do. So if Charles always reports a 90% confidence interval that's far too optimistic, we could help adjust it automatically next time. This would also allow us to aggregate different opinions directly, essentially being like a mini prediction challenge. This would be a ways off though, and it really depends on what direction the product goes.

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#59

Post by evanb »

ozgooen wrote: post #57
evanb wrote: post #52

Earlier quoted context omitted.

You should be careful about committing too much to particular distributions being the "right" ones. For example, what if I know some variable is an odd integer between 1 and 11 inclusive with no support on any other real number? Just something to keep in mind when abstracting what a distribution is. edit: though as a short-hand for entry, Gaussian is usually a pretty good guess. Is there support for µ±σ instead of [l…

"Is there support for µ±σ instead of [low,high] in the works? " - There used to be. I'll be considering ways of adding it back. "Or support for numerical distributions?" - By numerical distributions do you mean discreet distributions: like, a 40% of being '8' and a 60% chance of being '6'? If so, the answer is no. However, if you use the ternary operator it is possible to do very simple versions of this now. We do su…

I meant more along the lines of a user-entered histogram. But that's roughly the same as what you're talking about. It does seem that such a thing must roughly correspond to some internal portion of Guesstimate, anyway. So for an advanced user to punch a distribution in would be handy. May be out-of-scope for this project? I guess really I'm looking for a way to error propagate my home-grown datasets :)

Re: Introducing Guesstimate, a Spreadsheet for Things That Aren’t Certain

#60

Post by vive-la-liberte »

ozgooen wrote: post #55
vive-la-liberte wrote: post #41

Earlier quoted context omitted.

Thanks for the prompt reply. Are you planning to open source all of it in the future or will it remain SaaS?

Right now the vast majority of it is open source. There is a component that is not: the rails server, but that's pretty tiny. The client can be developed on without that. If there's some interest I'm happy to make what's existing available. I can't make guarantees about the distant future. There's a ton of work I would love to see happen with Guesstimate, and my guess is that much of it would only be possible if it b…

I see. Thank you for having open sourced so much of it already and good luck with the project :)
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