The Envelope Paradox: What Does Maths Say?

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Discussion Overview

The discussion revolves around the Envelope Paradox, a mathematical problem involving two envelopes containing cash, where one envelope has twice the amount of the other. Participants explore the implications of expected value calculations when deciding whether to swap envelopes after revealing the amount in one. The conversation touches on theoretical reasoning, assumptions about distributions, and the nature of paradoxes in mathematics.

Discussion Character

  • Debate/contested
  • Mathematical reasoning
  • Conceptual clarification

Main Points Raised

  • Some participants argue that the expected value calculation suggests a benefit to swapping envelopes, citing a 50% chance of either a lower or higher amount in the second envelope.
  • Others challenge this reasoning, stating that the paradox relies on an assumption of a uniform distribution over infinitely many values, which they argue is not valid.
  • A participant proposes a modified version of the paradox involving unlimited swaps without looking inside the envelopes, questioning the implications of such a scenario.
  • Some participants express confusion over the logic of the paradox and the reasoning behind the expected value calculations, seeking clarification on the assumptions made.
  • There is a discussion about the implications of the paradox for Bayesian statistics and the use of improper priors.
  • One participant suggests that the reasoning for swapping is flawed unless one assumes a uniform distribution on natural numbers, which they argue does not exist.
  • Another participant emphasizes that the reasoning is independent of the envelope's contents, leading to a cycle of swapping that suggests an infinite expected gain.
  • Several participants express uncertainty about the validity of the original analysis and the assumptions regarding prior distributions.

Areas of Agreement / Disagreement

Participants do not reach a consensus on whether it is beneficial to swap envelopes. There are multiple competing views regarding the assumptions underlying the expected value calculations and the nature of the paradox itself.

Contextual Notes

Participants highlight limitations in the reasoning, particularly regarding the assumptions of uniform distributions and the implications of finite versus infinite values. The discussion reflects a lack of clarity on how to properly evaluate the expected outcomes based on the information available.

  • #31


Wow, you managed to make the probabilities add up to more than 1 in a really trivial way (n=0...).

Now, I seem to have read recently that it is provable that there is no prior probability distribution where it is *always* preferable to switch. I think you should work out those posteriors again, after making it a probability distribution in the first place, though.
 
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  • #32


matt grime said:
Wow, you managed to make the probabilities add up to more than 1 in a really trivial way (n=0...).

Sorry, that was just a typo. I fixed my post - try re-reading it now.
 
  • #33


DaveC426913 said:
Ok, we know this intuitively. It seems that the key is to find the flaw in the logic of the OP's analysis. Why does his math seem to show that switching will on average yield a better result?


Because one assumes a uniform prior (which is not really possible as pointed out earlier). But if it were then the expected amount of money in the envelope would have to be infinite. So, if you only find a finite amount of money in the envelope, you should switch. :smile:
 
  • #34


Count Iblis said:
Because one assumes a uniform prior (which is not really possible as pointed out earlier). But if it were then the expected amount of money in the envelope would have to be infinite. So, if you only find a finite amount of money in the envelope, you should switch. :smile:

I think that this is a more satisfying way of stating the resolution than to simply point out that a uniform distribution with infinite support is not technically allowed. I.e., if the expected return under not switching is infinity, then the fact that switching provides 1.25 times the expected return does not actually recommend switching, since 1.25*infinity is still just infinity, so either strategy has the same expected return.
 
  • #35


If I open an envelope and see 100$, my expected return from swapping is between 50$ and 200$ -- i.e. not infinite.
 
  • #36


gel said:
Sorry, that was just a typo. I fixed my post - try re-reading it now.

I believe you now got the version where you're taking the difference between two random variables with infinite means.
 
  • #37


matt grime said:
I believe you now got the version where you're taking the difference between two random variables with infinite means.

The variables X and Y in my post do have infinite means. However, the conditional distributions have finite means. So, once you open one envelope it makes sense to ask what the expected return from opening the other envelope is, and E(X|Y) >= 2Y, E(Y|X) >= 2X.
 
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  • #38


As far as I can tell, the explanation of this is that since the expected amount you get is infinite (before peeking), then this means you shouldn't apply the rules of conditional probability, as things demonstrably go funky. Although there are examples where it will work, and some will find that explanation troublesome.
 
  • #39


I don't think it matters if the distributions have infinite mean. You can still use conditional probabilities just fine.
Here, we have E(Y|X)>= 2X and E(X|Y) >= 2Y, suggesting that it is always preferable to switch. If X and Y had finite mean then you could use the tower law to get E(Y) >= 2E(X) and E(X) >= 2E(Y) >= 4E(X). The only way is if E(X) and E(Y) are both infinite (or zero).

So the paradox can only occur with infinite means for the variables. The conditional expectations do still exist though.

And I wouldn't say that you shouldn't use conditional expectations of variations of variables with infinite mean. It can be very useful in many cases. What you have to be careful about is taking expectations of variables with infinite mean.
 
  • #40


So the paradox can only occur with infinite means for the variables

Well I suppose if you were playing a gme with an expected outcome of infinity then you'd be pretty pissed if you got any finite amount /joke. Does that example prove that some people are never satisfied?
 

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