6 ms·

You know, I never know what to make of that logic - what if that tiny probability was exactly this one time? It's not like we saw it happen twice, and it could

You know, I never know what to make of that logic - what if that tiny probability was exactly this one time? It's not like we saw it happen twice, and it could happen at some point. To my gut it seems you can't really know until you have other positive or negative observations. I wonder if someone has compiled a list of very improbable events that have been observed.

eli 11y ago
I get what you're saying, but 2^-80 is very VERY improbable. Hitting it once is equivalent to a merely "very unlikely" event like winning powerball happening multiple times in a row.
Lazare 11y ago
We happily incarcerate and (for countries that do so) execute people based on much weaker evidence. 2^-80 is absurdly small, to the point that essentially any other possibility is more likely. You say you want to see it twice, but one data point with an error rate of 1 in 2^80 is, statistically, about a billion times more convincing than a million observations with an error rate of 1 in a million. (That being said, there are a lot of of explanations that don't involve malice, including honest error, bugs in any of the software products involved in the process, etc. But no, I don't believe that this was a 1 in 2^80 fluke.)
marvin 11y ago
The likelihood of 1/2^80 is on the same order as me picking out a thousand grains of sand from the Sahara desert, spreading them randomly out through the desert and having you pick out those exact thousand grains of sand. It's a practical impossibility, a philosophical exercise.
- xyzzyz 11y ago
  No, it's not the same order. 1/2^80 is the same order as the likelihood of as picking 1000 grains out of 1010, and I'm sure you'll agree that Sahara has more grains that 1010. However, if you picked a single grain from Sahara desert, you'll be only 2 or 3 orders of magnitude off, so one could say that 2^-80 is only slightly easier than finding a particular grain in a Sahara desert.
- tika 11y ago
  Yes, but 1/2^80 is ridiculously large compared to 1/2^1024.
xyzzyz 11y ago
2^-80 (~10^24) is is about as likely as being hit by a meteorite (~10^-16)[1] at exactly the same moment you are learning that you won the Powerball (~10^-8). Alternatively, it is as likely as winning Powerball in three consecutive drawings. [1] - https://what-if.xkcd.com/19/ https://what-if.xkcd.com/19/
- frgewut 11y ago
  A person was hit by a meteorite [1] [1] http://www.telegraph.co.uk/news/science/space/5511619/14-year-old-hit-by-30000-mph-space-meteorite.html http://www.telegraph.co.uk/news/science/space/5511619/14-yea...
Sharlin 11y ago
There are countless other possible causes that are much more probable than M-R returning a false positive. What should we do about all of them? Start ruling them out, one by one, sure, but in which order? Common sense says we should do it in the order of decreasing prior probability. The hypothesis "M-R returned a false positive" is there somewhere, in the space of all possible hypotheses, and we'll surely encounter it after all other more likely alternatives are exhausted. I bet we don't have to go that far.
saurik 11y ago
For many years, in the computer science lab at the college where I sort of work, there was a "serious joke" written on the wall which said, with much better wording and some math to back it up, that the difference between a mathematician and an engineer is that the former was more concerned that a probabilistic primality test could inherently fail while the latter was more concerned that even a guaranteed algorithm was actually more likely to return the wrong answer because the computer was hit by a cosmic ray while it was determining if the number were prime.
- lultimouomo 11y ago
  Probably a quote from SICP: https://mitpress.mit.edu/sicp/chapter1/footnode.html#2413 https://mitpress.mit.edu/sicp/chapter1/footnode.html#2413
ikeboy 11y ago
https://blogs.msdn.microsoft.com/oldnewthing/20160114-00/?p=92851 https://blogs.msdn.microsoft.com/oldnewthing/20160114-00/?p=...
Jach 11y ago
My own list is of length 1 as a category of events. Back in July (it's a bit harder now), the odds that someone's calculated sha256 sum solved a new bitcoin block were around 2^-68. This very tiny probability event was observed on average once every 10 minutes. 2^-80 is absurdly small. But that only means something useful if the number of attempts isn't absurdly large.
makmanalp 11y ago
Wow - this has got to be my most downvoted comment. I can't edit the original anymore, so here's my update: I guess the harsh reaction came from the fact that I didn't define the scope very well: My question wasn't in reference to M-R specifically, just in general. I understand that in this case it makes sense to look at likelier causes (see Sharlin's response). My point was that it's interesting to look at what happens (or what our reaction is) when very very very improbable events do happen. It seems weird to go with the assumption that because something is extremely unlikely that it won't happen. When I roll a dice 20 times, I get a particular arrangement of numbers. Given the total number of arrangements possible, that particular arrangement is extremely unlikely, yet I just got it. A guy got struck by lightning 7 times (https://en.wikipedia.org/wiki/Roy_Sullivan https://en.wikipedia.org/wiki/Roy_Sullivan). The odds of any person getting struck by lightning is 1 in 10000. Seven times in a row is 1 in 2^93. But then when you start drilling down, you see that he's a park ranger, and that he's out while lightning happens, which makes the probability that he'll get struck much higher. If I had phrased the question to you asking what the likelihood of any given person in the world being struck seven times was, you could have calculated the former and said 2^-93 is such a small probability that it's not worth thinking about - and yet here is Roy Sullivan, so there's some sort of conflict in my logic. What's wrong with the former calculation? Why is it that for any given person the probability is 2^-93 but for Roy it's somehow different, even though he is a "given person"? Is it that the 1 in 10000 number was wrong? But then if we look at all the people who never once got struck, it seems about right. If we inflate that number to 1 in 100 to make Roy likelier to get 7 in a row, then it seems everyone also should be getting shocked more often at least once or twice. Or maybe it's that somehow the probability changes when we have more information and those two numbers and situations are not comparable on an absolute scale. Maybe if you get hit twice then you're much likelier to get hit again because you're probably in some dangerous location - but how was I to know to factor this in? It seems that it's very much about how you calculate the probability. Who knows what other hidden factors could be wildly affecting the true value of the probability? That also makes me think - is there even such a thing as the "true" or inherent probability of an event happening? edit: Or maybe it's the law of large numbers - given enough "trials" or in this case lightning events with people around, even something with an absurdly small probability is bound to happen eventually. But then why do we never factor that in and always just call it a day with 10000^7?
jibalt 11y ago
Your gut is bad at statistics.

eli 11y ago

I get what you're saying, but 2^-80 is very VERY improbable. Hitting it once is equivalent to a merely "very unlikely" event like winning powerball happening multiple times in a row.

Lazare 11y ago

We happily incarcerate and (for countries that do so) execute people based on much weaker evidence. 2^-80 is absurdly small, to the point that essentially any other possibility is more likely. You say you want to see it twice, but one data point with an error rate of 1 in 2^80 is, statistically, about a billion times more convincing than a million observations with an error rate of 1 in a million. (That being said, there are a lot of of explanations that don't involve malice, including honest error, bugs in any of the software products involved in the process, etc. But no, I don't believe that this was a 1 in 2^80 fluke.)

marvin 11y ago

The likelihood of 1/2^80 is on the same order as me picking out a thousand grains of sand from the Sahara desert, spreading them randomly out through the desert and having you pick out those exact thousand grains of sand. It's a practical impossibility, a philosophical exercise.

xyzzyz 11y ago
No, it's not the same order. 1/2^80 is the same order as the likelihood of as picking 1000 grains out of 1010, and I'm sure you'll agree that Sahara has more grains that 1010. However, if you picked a single grain from Sahara desert, you'll be only 2 or 3 orders of magnitude off, so one could say that 2^-80 is only slightly easier than finding a particular grain in a Sahara desert.
tika 11y ago
Yes, but 1/2^80 is ridiculously large compared to 1/2^1024.

xyzzyz 11y ago

2^-80 (~10^24) is is about as likely as being hit by a meteorite (~10^-16)[1] at exactly the same moment you are learning that you won the Powerball (~10^-8). Alternatively, it is as likely as winning Powerball in three consecutive drawings. [1] - https://what-if.xkcd.com/19/ https://what-if.xkcd.com/19/

frgewut 11y ago
A person was hit by a meteorite [1] [1] http://www.telegraph.co.uk/news/science/space/5511619/14-year-old-hit-by-30000-mph-space-meteorite.html http://www.telegraph.co.uk/news/science/space/5511619/14-yea...

Sharlin 11y ago

There are countless other possible causes that are much more probable than M-R returning a false positive. What should we do about all of them? Start ruling them out, one by one, sure, but in which order? Common sense says we should do it in the order of decreasing prior probability. The hypothesis "M-R returned a false positive" is there somewhere, in the space of all possible hypotheses, and we'll surely encounter it after all other more likely alternatives are exhausted. I bet we don't have to go that far.

saurik 11y ago

For many years, in the computer science lab at the college where I sort of work, there was a "serious joke" written on the wall which said, with much better wording and some math to back it up, that the difference between a mathematician and an engineer is that the former was more concerned that a probabilistic primality test could inherently fail while the latter was more concerned that even a guaranteed algorithm was actually more likely to return the wrong answer because the computer was hit by a cosmic ray while it was determining if the number were prime.

lultimouomo 11y ago
Probably a quote from SICP: https://mitpress.mit.edu/sicp/chapter1/footnode.html#2413 https://mitpress.mit.edu/sicp/chapter1/footnode.html#2413

ikeboy 11y ago

https://blogs.msdn.microsoft.com/oldnewthing/20160114-00/?p=92851 https://blogs.msdn.microsoft.com/oldnewthing/20160114-00/?p=...

Jach 11y ago

My own list is of length 1 as a category of events. Back in July (it's a bit harder now), the odds that someone's calculated sha256 sum solved a new bitcoin block were around 2^-68. This very tiny probability event was observed on average once every 10 minutes. 2^-80 is absurdly small. But that only means something useful if the number of attempts isn't absurdly large.

makmanalp 11y ago

Wow - this has got to be my most downvoted comment. I can't edit the original anymore, so here's my update: I guess the harsh reaction came from the fact that I didn't define the scope very well: My question wasn't in reference to M-R specifically, just in general. I understand that in this case it makes sense to look at likelier causes (see Sharlin's response). My point was that it's interesting to look at what happens (or what our reaction is) when very very very improbable events do happen. It seems weird to go with the assumption that because something is extremely unlikely that it won't happen. When I roll a dice 20 times, I get a particular arrangement of numbers. Given the total number of arrangements possible, that particular arrangement is extremely unlikely, yet I just got it. A guy got struck by lightning 7 times (https://en.wikipedia.org/wiki/Roy_Sullivan https://en.wikipedia.org/wiki/Roy_Sullivan). The odds of any person getting struck by lightning is 1 in 10000. Seven times in a row is 1 in 2^93. But then when you start drilling down, you see that he's a park ranger, and that he's out while lightning happens, which makes the probability that he'll get struck much higher. If I had phrased the question to you asking what the likelihood of any given person in the world being struck seven times was, you could have calculated the former and said 2^-93 is such a small probability that it's not worth thinking about - and yet here is Roy Sullivan, so there's some sort of conflict in my logic. What's wrong with the former calculation? Why is it that for any given person the probability is 2^-93 but for Roy it's somehow different, even though he is a "given person"? Is it that the 1 in 10000 number was wrong? But then if we look at all the people who never once got struck, it seems about right. If we inflate that number to 1 in 100 to make Roy likelier to get 7 in a row, then it seems everyone also should be getting shocked more often at least once or twice. Or maybe it's that somehow the probability changes when we have more information and those two numbers and situations are not comparable on an absolute scale. Maybe if you get hit twice then you're much likelier to get hit again because you're probably in some dangerous location - but how was I to know to factor this in? It seems that it's very much about how you calculate the probability. Who knows what other hidden factors could be wildly affecting the true value of the probability? That also makes me think - is there even such a thing as the "true" or inherent probability of an event happening? edit: Or maybe it's the law of large numbers - given enough "trials" or in this case lightning events with people around, even something with an absurdly small probability is bound to happen eventually. But then why do we never factor that in and always just call it a day with 10000^7?

jibalt 11y ago

Your gut is bad at statistics.