The Puzzle of Probability Itself

Yes, and that is exactly the situation that probability is supposed to describe. If the question is insufficient to specify the limits of what is unknown, then the probabilities of different outcomes cannot be calculated. The question can be rephrased as, "Given that I know [list of factors], that I do not know [second list of factors], and that I do not know [list of outcomes], what are the probabilities of the different outcomes?" Some of this is embodied in the statement that "The dice are fair," which is itself a statement about probability.
Dave

Very true and I think a critical aspect - the self-referential bit. This comes up a lot when moving from thought problems to the real world.

"How do you know the die is fair?"
"Because the outcomes are symmetrical."
"How do you know they are symmetrical?"
"Because I can't distinguish between them beforehand."
"But you can distinguish between them afterwards?"
"Yes."
"So the final outcome is not symmetrical?"
"Yes, symmetry is broken during the procedure that generates the outcome."
"But how do you know the procedure isn't tainting the outcome?"
"The procedure is fair."
"How do you know? Since the procedure cannot be symmetrical or you wouldn't get any outcome at all - the very purpose is to break symmetry."
"Yes, but the symmetry is broken over the set of all equally possible outcomes, without preference for any particular one."
"How can I be assured of that?"
"Because I used a fair die."

(That was fun. I just typed out a conversation I had with myself. Probably time for a nap.)
 
Very true and I think a critical aspect - the self-referential bit. This comes up a lot when moving from thought problems to the real world.

Yes, however we do observe that some dice are arbitrarily close to being fair from following the distribution of results when rolling them.

Dave
 
It is interesting that you differentiate a red six and a blue six from a blue six and a red six (answer 5, which no one likes yet, depends on this too). Where did the ordering element come in? Is it because Sally shows one dice and has a choice?

Suppose Sally merely stated, "At least one of the dice is a six" (but didn't show any). Would this change alter your analysis? (Keeping the colors in play.)
We know that with red and blue dice there are (6 x 6) = 36 possible combinations we could roll. We know that Sally shows us one die. We don't know why she chose it. For each of the 36 outcomes she might show us either the red or the blue, so that makes (2 x 36) = 72 possible outcomes in all.

We can reject all of those which don't result in her showing us a six. That leaves twelve possibilities: Six where Sally shows us a red 6 and the blue is any number and six more where she shows us a blue 6 vice versa. Two out of those twelve cases have the other number being a 6.
 
Yes, however we do observe that some dice are arbitrarily close to being fair from following the distribution of results when rolling them.

Dave

I'm curious how you might actually do this. How is it that you would define "fair" since any sequence of rolls whatsoever could occur, whether the die is fair or not.

What you might mean is something like, "I can conceive of no bias that would generate the sequence which occurred, therefore I will assume there is no bias." I think the shoe, in this instance goes on the other foot and we start with the assumption of not-biased instead of the assumption of biased.

ETA: I don't mean our assumption is without justification. We use symmetry to generate the assumed not-biased condition.
 
If I state the problem with enough specificity, I get answer 1. Why? Because enough specificity gives me all the relevant details (Sally's hand position, the forces on the dice, the constitution of the surface they land on, etc. ad nauseum) and any notions of less than certainty (probability one or zero) evaporates thereby.

What you seem to be asking for is only enough specificity to differentiate between certain answers and then stop.

No, I don't agree. You can ask a very specific question about a random event and get an accurate answer about its probabilities. All we need to know about the roll of the dice is that we can regard it as fair and random.
 
I'm curious how you might actually do this. How is it that you would define "fair" since any sequence of rolls whatsoever could occur, whether the die is fair or not.

By noting that, over a sufficiently large number of rolls, the outcomes are statistically indistinguishable from what would be expected in the assumption that all six outcomes are equally probable but randomly distributed. Yes, it's self-referential, but the same is true of any predictive theory; we take a set of observations, construct a theory that predicts future observations, and assess the quality of the theory by how well those future observations agree with it.

Dave
 
I'm curious how you might actually do this. How is it that you would define "fair" since any sequence of rolls whatsoever could occur, whether the die is fair or not.

Any sequence at all might occur but, as the number of rolls gets larger, the probability of a strong bias toward one result appearing by chance gets less. Of course you wouldn't expect to end up with exactly the same number of rolls of each result either. That would be most unlikely too. What you can do, for a large number of rolls, is calculate the probability that the sequence you get could have been produced by a fair die.

Google presented me with this which nicely illustrates the point: http://timothyweber.org/node/255
 
By noting that, over a sufficiently large number of rolls, the outcomes are statistically indistinguishable from what would be expected in the assumption that all six outcomes are equally probable but randomly distributed. Yes, it's self-referential, but the same is true of any predictive theory; we take a set of observations, construct a theory that predicts future observations, and assess the quality of the theory by how well those future observations agree with it.

Dave

I'm proposing that any sequence whatsoever meets this condition. It is mathematically possible to roll any arbitrarily long sequence of all ones with a fair die.

Further, if you set some cut-off, that cut-off is just as arbitrary since any actual sequence you get has the same probability as any other. I suggest what actually happens is a matter of subjective taste influenced by our ability to be surprised set against our ability to imagine what biases are possible. I also think this is the best we can do under the circumstances (only having one reality to observe).

ETA: I should say I'm not against the assumption of bias-free (or nearly so) random chance. I rather like it. It's just that it is an assumption in my view.
 
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I'm proposing that any sequence whatsoever meets this condition. It is mathematically possible to roll any arbitrarily long sequence of all ones with a fair die.

So the question becomes what is the probability that this sequence could have been produced by a fair die?

So, rather like the difference between jury service and courtroom drama, you don't get told at the end if you guessed right. You can only weigh up the probabilities based on the evidence and then decide. Of course with dice you can collect arbitrarily large samples of evidence, which helps.:)
 
Any sequence at all might occur but, as the number of rolls gets larger, the probability of a strong bias toward one result appearing by chance gets less. Of course you wouldn't expect to end up with exactly the same number of rolls of each result either. That would be most unlikely too. What you can do, for a large number of rolls, is calculate the probability that the sequence you get could have been produced by a fair die.

Google presented me with this which nicely illustrates the point: http://timothyweber.org/node/255

That is a good article (as well as the one earlier on the same subject) but how would it handle a die that is biased to always roll this sequence? 1,2,3,4,5,6,1,2,3,4,5,6...? My die would pass all the tests with flying colors.

That's just a trivial objection. There are more fundamental ones.
 
So the question becomes what is the probability that this sequence could have been produced by a fair die?

So, rather like the difference between jury service and courtroom drama, you don't get told at the end if you guessed right. You can only weigh up the probabilities based on the evidence and then decide. Of course with dice you can collect arbitrarily large samples of evidence, which helps.:)

That's why the symmetry idea is so powerful. It gets us past the tests - or better, adds another type of test from a different direction.
 
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That is a good article (as well as the one earlier on the same subject) but how would it handle a die that is biased to always roll this sequence? 1,2,3,4,5,6,1,2,3,4,5,6...? My die would pass all the tests with flying colors.

That's just a trivial objection. There are more fundamental ones.

Counting up how often you roll sixes etc is only one trivial test.

I think it would be a simpler task to design tests that analyse the results looking for improbable patterns than it would be to build loaded dice which could produce them.
 
That is a good article (as well as the one earlier on the same subject) but how would it handle a die that is biased to always roll this sequence? 1,2,3,4,5,6,1,2,3,4,5,6...? My die would pass all the tests with flying colors.

No, it would pass one particular test with flying colours. There are others that can be applied; for example, what proportion of 1's are followed by which other number, or what is the longest sequence of identical results in a series of rolls of a given length. The latter can suggest a non-random sequence, for example, if the longest sequence of identical results is too short.

Dave
 
Counting up how often you roll sixes etc is only one trivial test.

I think it would be a simpler task to design tests that analyse the results looking for improbable patterns than it would be to build loaded dice which could produce them.

No, it would pass one particular test with flying colours. There are others that can be applied; for example, what proportion of 1's are followed by which other number, or what is the longest sequence of identical results in a series of rolls of a given length. The latter can suggest a non-random sequence, for example, if the longest sequence of identical results is too short.

Dave


I have a new die in mind. It's quite advanced - a remote controlled, programmable die. Of course, on a surface inspection it looks normal.

I take my die and program it to duplicate the numbers in a table of random numbers. Does it pass all the tests? Is it a fair die?

(I fear we are drifting away from the meaning of probability now though.)
 
I have a new die in mind. It's quite advanced - a remote controlled, programmable die. Of course, on a surface inspection it looks normal.

I take my die and program it to duplicate the numbers in a table of random numbers. Does it pass all the tests? Is it a fair die?

(I fear we are drifting away from the meaning of probability now though.)

What you're testing is the randomness of the process by which you generated the table of numbers. How good is that?

Of course, if you generated them by recording the results of a series of dice rolls...

Dave
 
I think I may have lost track of the variation you are referring to. In my conception there is only one "rolling event" the original randomizing process. By the time I get additional information, all the dice are fixed.

Forgive me if I misunderstood. (Your sig quote applies to me here.)
In your original posting, you are describing an event that includes multiple dice rolls, and the probability of the event is the probability of the dice rolls together. You state:
She shows one is a six. What is the probability that the other one is a six?

In this case, whether the dice are rolled simultaneously or not, the probability you are asking about is that of the series, not of the individual event. I do not see any reason to differentiate this from the question of whether the rolling of a die on the moon makes a difference on what you find when you roll one on the table in front of you.

I would suggest that the chance of the unrevealed die coming up as a six is one in six. The chance that this will seem extraordinary depends on the status of all the dice in the set.
 
If I read last week that Hillary has a 60% chance of winning the election, and I read this week that her chances have improved to 80%, it feels to me like that's a real difference - a factual, measured difference. And yet, after the election, when I know the outcome, it's hard to look back with any seriousness and think those numbers meant much other than I didn't know what the outcome would be.

It's easy to understand those numbers, assuming they were based on polls. The polls are based on samples. Samples have uncertainty. Take a simplified situation, like the race between two candidates for a US Senate seat, where a simple majority of votes determines the winner. A polling firm polls 500 voters and finds that 52% of them say they'll vote for the Democratic candidate. As an estimate of how the population of voters will vote, the polling firm's 52% is only accurate to about ± 4%. The Democrat will win if the true proportion of voters who will vote for him is at 50%. A little math shows that, given the poll result of 52% ± 4%, the probability that the true percentage is at least 50% is about 83%. So, based on this poll, the Democrat has an 83% chance of winning.

Later, say another polls of 500 voters is conducted and finds that 53% of voters now say they'll vote for the Democratic candidate. The same math shows that the Democrat's chances have improved to 92%.

So, the bottom line is that the probability of winning at any point in time directly depends on the proportion of votes the polls say favor the candidate.
 
Here's a problem making the rounds about probability. I mention it not to get the "correct" answer, but as a target to invite conversations about what we should take probability to mean.

Sally rolls two dice (6-sided, assumed fair). She shows one is a six. What is the probability that the other one is a six?

1) Either zero or one.
2) 1/2
3) 1/6
4) 1/11
5) 1/12
6) 1/36
7) Make up another answer or even reject the premise.

This is a variant of classic probability problem (usually stated in terms of sons or daughters). The correct answer is 1/11, as you proved, by enumerating the sample space, here:

Once you see that one of the dice is a six, you know the set we are dealing with is: {1,6; 2,6; 3,6; 4,6; 5,6; 6,6; 6,1; 6,2; 6,3; 6,4; 6,5}

Don't believe your own results? Let's do a simulation. The following code draws 1 million random samples of a simulated pair of fair 6-sided dice, and computes the proportion of samples where both die came up 6 among those where at least one die came up 6:

Code:
d1 <- sample.int(6, 1e6L, replace=TRUE)
d2 <- sample.int(6, 1e6L, replace=TRUE)
sum(d1 == 6 & d2 == 6) / sum(d1 == 6 | d2 == 6)
# [1] 0.09087517

The result, shown in the last line, is 1/11 to within a small sampling error.

However, there is actually an ambiguity in the wording of the problem. The probability that the second die is a 6, depends on how Sally came to learn that one die was a 6. The 1/11 probability is assumes that she looked at both dice, saw that at least one of the was a 6 and then asked you to compute the probability that the other one was also a 6. In this case, the sample space if the set of 11 outcomes in which at least one of the dice is a 6—that is, the sample space you enumerated. Those outcomes are equally likely, and so the answer is 1/11.

On the other hand, what if Sally only looked at one of the dice, saw that it was a six, and that no matter what outcome she saw, she would not look at the other die. Given those conditions, she then asked you to compute the probability that the other die is a six. Now, the sample space is simply {1, 2, 3, 4, 5, 6}. And since all 6 possible outcomes are equally likely, the answer is 1/6.

1) The outcome is already determined and in fact, was determined long ago as each cause led to a subsequent effect until a combination of material events plus the laws of nature resulted in the pre-determined outcome. The results are fixed and must be either zero or one, depending on those prior causes. The fact that we don't know the details is irrelevant - only adding an unnecessary subjective element. In the actual world the dice have already been rolled and their state is a matter of certain, historical fact.

That logic is unproductive. It doesn't help you win at poker, for example, filter the spam from your email, or find a lost hiker. So, it's pretty useless to think of probabilities of events that have already happened, but whose outcome you don't know, as having to be 0 or 1.

2) True, the results were determined, but the question is about my own estimation and state of knowledge. Since I cannot determine between zero or one and have no insight into the prior determinants, I must average the two and state "1/2".

This answer is indefensible. You might not know what the outcome is, but you know what a 6-sided die is, and it isn't something that has a 50-50 chance of landing 6. You have equal ignorance about each of the 11 possible outcomes, and so your subjective probability of each outcome is 1/11.

6) (I picked this one before I found it lacking.) The relevant randomizing event is the original roll. Anything after is tainted by agency (Sally's choices). We know that rolling two die will generate 36 possibilities, only one of which is a pair of sixes. Therefore, keeping only the original roll "pristine" we get 1/36.

This is just nonsense. You were given some information about the outcome. This restricts the sample space to those outcomes of which at least one die showed a six. There are 11 of them, not 36.
 
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Hu. No. How you ask the question should not change the answer, unless you are monkeying with people and try to cheat/play with their mind them (e.g. riddle, tv games, advertising, marketing , polls, politics etc...) which is why certain domain get bad reps.

How you ask a question should never change the answer in pure math.

Which question you ask should change the answer though.
 
In your original posting, you are describing an event that includes multiple dice rolls, and the probability of the event is the probability of the dice rolls together. You state:

In this case, whether the dice are rolled simultaneously or not, the probability you are asking about is that of the series, not of the individual event. I do not see any reason to differentiate this from the question of whether the rolling of a die on the moon makes a difference on what you find when you roll one on the table in front of you.

I would suggest that the chance of the unrevealed die coming up as a six is one in six. The chance that this will seem extraordinary depends on the status of all the dice in the set.

So long as Sally could show either die as a six, then yes, it does not matter whether they are thrown as a pair or where (the moon) they are thrown. Because she selects a six to show however, the dice are linked (for one of the arguments to work). So, for example, she couldn't toss one last year and show it immediately. That would give you more information than waiting until both had been thrown.
 

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