If you want to throw around ad hominem insults, nobody can stop you.
That doesn't make them justified.
For the record, I am very aware that one cannot define things like expected values and probabilities without a probability distribution. I am also painfully aware that many things that look like they might reasonably make probability distributions (eg a uniform distribution on the real numbers), don't.
But the problem that I'm giving here can readily be precisely worded in a way that entirely avoids those issues. Here is the precise wording:
Suppose that you have 2 different numbers x and y in 2 envelopes, written down in decimal form. Let us define the following experiment. You will randomly hand me one of your two envelopes, I will look at it, and I will tell you whether I think you handed me the larger. Is there an algorithm that I can use, which guarantees that the probability of my being right, given x and y (which I do not know) and my algorithm, is strictly better than 50%?
Note the following critical details:
- The numbers x and y are part of the experiment. How they came to be is not part of the question asked, and therefore questions about how to choose them do not enter into the problem.
- I lack sufficient information to calculate the probability of being correct. In particular I don't know what x and y are.
- The algorithm that I use must work no matter what x and y happen to be. If my technique depends on assumptions about x and y, then I have not succeeded because you might have a pair that my technique does not work for.
If you relax *any* of these conditions even slightly then the result tends to quickly becomes either false or undefined. The result is very fragile and precise.
Now I won't go through the full reasoning again here. But if you're interested, this was discussed extensively on sci.math over a decade ago. For a particularly clear explanation, see this post by Bently Preece. | [reply] |

Congratulations, you've finally exposed yourself. The original problem tou link to is based on real intervals derives its 50% result from the fact that any two real intervals, even one unbounded versus one bounded, have the same cardinality. It's source is first year maths where students are introduced to such concepts before getting into the finer points of real number analysis. Your new version (accidental?) with natural numbers doesn't work the same way. It is not insulting to expose your mistakes, the only damage is what you do to yourself by pretending with substantial futility and tell-tale superwaffle to understand more than you actually do.
| [reply] |

Any post as full as yours is of plausible-seeming but ridiculously off-base non-sequitors is evidence either of profound ignorance or deliberate trolling. It doesn't matter which is the case, both possibilities indicate that I should not waste further effort on you.
| [reply] |