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Product of all binomial coefficients
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Product of all binomial coefficients
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Product of all binomial coefficients
Melanzio, now, you can cite your own question: @MISC {484413, TITLE = {Product of all binomial coefficients}, AUTHOR = {Melanzio (mathoverflow.net/users/528900/melanzio)}, HOWPUBLISHED = {MathOverflow}, NOTE = {URL:mathoverflow.net/q/484413 (version: 2024-12-18)}, EPRINT = {mathoverflow.net/q/484413}, URL = {mathoverflow.net/q/484413} }
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Product of all binomial coefficients
@R.vanDobbendeBruyn, it's hard to get shorter than Max Alekseyev's answer, but I give a bijection below for fun.
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Can I find $n$ points on the boundary of an $n$-dimensional ball with certain properties?
Of course, there's a sort of dual way to generalize the $n=2$ case: we take hyperplanes passing through $v$ and tangent to the ball, and ask if as few as $n$ such hyperplanes can contain the ball in the intersection of their halfspaces. In other words, the "front-on" view of the two approaches looks like en.wikipedia.org/wiki/Method_of_exhaustion
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Finite verification for theorems due to Busy Beaver numbers
Yes, it turns out the statement is trivial, but the "nontrivial intuition" the question is trying to capture is interesting, and addressed nicely in Sam Hopkins' comment. Namely, if we had an oracle for BB(n), we could automate the proof/disproof of any well-defined claim.
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Why sum of samples without replacement is more concentrated than with replacement?
Can one show that the $y_1,\dots,y_n$ are negatively associated random variables? Then since the marginals are the same, it would imply that any Chernoff-type bound that applies to the x's also applies to the y's.
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Optimally betting a beta-biased coin
Another question is if we can prove monotonicity - if it is optimal to bet with $h$ heads and $t$ tails, is it optimal to bet with $h' \geq h$ heads and $t' \leq t$ tails?
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Optimally betting a beta-biased coin
Can we get anything by writing down the optimal strategy via backward induction? E.g. we can define $f(h,t)$ to be the EV of betting at the current round $n = h+t$ given there have been $h$ heads and $t$ tails, followed by playing optimally thereafter; and $g(h,t)$ to be the EV of not betting and playing optimally thereafter; and $V(h,t) = \max\{f(h,t), g(h,t)\}$, and we can write $f(h,t)$ and $g(h,t)$ in terms of $V(h+1,t)$ and $V(h,t+1)$. Etc.
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How to optimally bet on a biased coin?
For the record, I agree with Will that this proof is not correct. And the reason is roughly that one should consider betting even when this round's EV is negative, if the EV of the next round conditioned on a heads this round is positive. For example, if $p$ were uniformly either $0$ or $0.9$, this answer would say to wait to bet until you see a head, but betting immediately is much better, because in the world where $p=0.9$, you usually have a 2x or 4x head start on an approaching-infinitely-large EV, which is worth giving up an additive $1$ in the world where $p=0$.
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Points based partial ranking
Anyway, there is the voting button.
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Points based partial ranking
I think we should be slow to confidently dismiss questions outside our areas of familiarity, even when there are clear problems with the question.
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Using Busy Beavers to prove conjectures
@TimothyChow It may also help to mention that to prior-me, and presumably other untrained people, intuitively there can appear to be a difference between "BB(n) has a well-defined value in ZFC" and "ZFC proves BB(n) = m for some m".
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Using Busy Beavers to prove conjectures
@TimothyChow to me, that appears to confuse two notions of determinable, i.e. of course BB(n) is not computable by reduction from halting, but it's much less obvious that BB(n) could be independent of ZFC.
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Is a bounded convex function $g$ that is non-negative on this particular convex set also non-negative on the its closure?
What is an example of a point in $S \setminus T$?
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Using Busy Beavers to prove conjectures
@WillSawin speaking for myself, my intuition that BB(n) is determinable would be that every Turing Machine either halts or does not, and there is a finite set of Turing Machines of size n. (See my previous comment for how I learned the flaw in this reasoning.)