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For dices that we cannot distinguish we have learned in class, that the correct sample space is $\Omega _1 = \{ \{a,b\}|a,b\in \{1,\ldots,6\} \}$, whereas for dices that we can distinguish we have $\Omega _2 = \{ (a,b)|a,b\in \{1,\ldots,6\} \}$.

Now here's the apparent paradox: Suppose we have initially two identical dices. We want to evaluate the event that the sum of the faces of the two dices is $4$. Since $ 4=1+3=2+2$, we have $P_1(\mbox{Faces}=4)=\frac{2}{|\Omega_1|}=\frac{2}{21}$. So far so good. But if we now make a scratch in one dice, we can distinguish them, so suddenly the probability changes and we get $P_2(\mbox{Faces}=4)=\frac{3}{|\Omega_2|}=\frac{3}{36}=\frac{1}{12}$ (we get $3$ in the numerator since $(3,1) \neq (1,3$)).

Why does a single scratch change the probability of the sum of the faces being $4$ ?

(My guess would be that either these mathematical models, $\Omega _1,\Omega _2$, don't describe the reality - meaning rolling two dices - or they do, but in the first case, although the dices are identical we can still distinguish them, if we, say, always distinguish between the left dice and the right, so applying the first model was actually wrong. But then what about closing the eyes during the experiment ?)

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    Suppose that the dice are colored red and green respectively and thus are distinguishable to you but not to me since I am red-green colorblind. Should the probabilities that we compute be different or the same? What if we try an empirical test of rolling the dice $1680$ times to see how well our model approximates the real world? Will we have rolled $4$ _approximately_ $1680\times\frac{2}{21}=160$ times as per your model or $1680\times\frac{1}{12}=140$ times as per my model?2012-03-06

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In the case where you don't distinguish between the dice, it is fine to use a sample space that consists of unordered pairs. But the price you pay for that is that the elements in $\Omega_1$ not equally probable.

In particular, it is not valid to compute probabilities simply by counting relevant elements of $\Omega_1$ and divide by its total cardinality $|\Omega_1|$.

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    @user9352: Correct -- there's nothing logically inconsistent about the idea of dice that behave in such "strange" ways. They just don't seem to occur in reality.2012-06-10
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The correct probability distribution for dice treats them as distinguishable. If you insist on using the sample space for indistinguishable dice, the outcomes are not equally likely. However, if you are doing quantum mechanics and the "numbers" become individual quantum states, indistinguishable dice must be treated using either Fermi or Bose statistics, depending on whether they have half-integer or integer spin.