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16:02
Yes exactly, basically, the idea of that fraction is so independent from the number of repeats that everytime you try to do it, you get a different fraction and it never converges to any nice pattern

It's as if each trial is an independent event, with a value of probability that is not fixed
@DavidZ I think it's a bit more than that. Your task is to prepare a bag full of plusses and minuses in such a way that no one, not even you, knows what the percentage of plusses is.
The problem is: no matter how deep you nest your random processes, there is always a best guess for the probability of pluses.
@Secret Now... if accept the negation of the Axiom of Choice, you can theoretically do this, but not in practice.
make sense
Ooooh, wait.
Suppose you use the results of your previous selection to choose what the distribution is for the next pick?
The law of large numbers says that any average you get from samples will converge to the true average with repeated sampling. I still don't get what we're looking for.
@ACuriousMind Can you find a selection process where you can't predict what that number will be?
16:06
@Slereah QFT has never raised the GDP.
Actually, what I just said might work, but it's easier in the non binary case. Every time you select a number, the next number will be selected from a probability distribution based on the number you just selected. However, I think that's still wrong somehow.
@barrycarter Well...e.g. the Cauchy distribution doesn't have a mean.
@ACuriousMind Yeah, and the alpha and beta distributions don't have SDs, but I'm not sure they count. Let me take a quick look at Cauchy
@ACuriousMind OK, so if you kept picking numbers from Cauchy and averaged them, the average would run off to +Infinity or -Infinity (depending on your pre-chosen fixed parameters?)
@ACuriousMind How
I don't believe that for a second.
@0celo7 Sort of like the martingale I'm guessing.
@0celo7 No finite mean.
16:13
Can you not integrate xP(x)?
@barrycarter No, I think it will actually converge to the median...
@0celo7 Exactly
@ACuriousMind If that's true, than that's the mean.
@barrycarter No, the mean doesn't exist, the integral is undefined.
@0celo7 Just because you can integrate P(x) and get a finite result, doesn't mean you can integrate x P(x) and get a finite result.
@ACuriousMind OK, the integral is undefined, but if you average enough samples, you get the median? (cough cough)
@barrycarter Proof?
16:15
@barrycarter It is just a hunch. I don't actually know what happens to sampling from the Cauchy distribution
@0celo7 WP the Cauchy distribution, although the Martingale is another example. 2^-i probability of getting i.
Perhaps it also just dances all over the place and never converges.
WP?
@0celo7 Wikipedia.
@ACuriousMind Stop personifying mathematics
16:16
@ACuriousMind Hmmm.... you might be making sense... but your argument would mean the Cauchy distribution is symmetric in values?
@ACuriousMind how do you know that
@ACuriousMind If what you're saying about dancing is true, you've found @Secret's answer. However, I believe that's literally impossible.
I think that "no mean" just means there's no finite mean.
@0celo7 Through a combination of intelligence and intuition.
I am this close to doing some actual mathematics and seeing what happens when you integrate the Cauchy PDF.
16:18
@barrycarter No, the integral for the mean is also not divergent in the sense that it would actually be infinte. you just can't assign a finite value to it (or rather, depending on your regularization, you can assign any value to it)
I.e. the integral does not converge
@ACuriousMind For a given fixed set of parameters, you're saying the integral does not converge?
Even if you would allow it to be $\infty$ or $-\infty$.
@barrycarter Yes
If what you guys said is true, then this really surprise me, because this cauchy distribution looks really ordinary in terms of shape
@ACuriousMind I must call shenanigans.
I mean the first thing that came to mind when I look at it is it looks like any bell curve lookign symmetric distribution
Guess I should not be fooled by deceptively simple looking shapes like these when questions like these came up in the future....
16:21
@ACuriousMind Pleasse give me some of that
@barrycarter Well, if you can integrate it, be my guest, but I'm pretty sure $xf(x)$ for $f$ the Cauchy distribution is just non-integrable.
Just choose the median at 0, then $f(x)$ is symmetric.
Hence $xf(x)$ is odd.
@ACuriousMind I call special case!
If the integral of $xf(x)$ existed, it would be zero.
I think that's a special case though.
@barrycarter You can always shift it inside the integral.
16:22
There are multiple parameters I think.
@ACuriousMind Tue distribution is even
So why isn't the integral zero
58 secs ago, by ACuriousMind
If the integral of $xf(x)$ existed, it would be zero.
I realize there are functions like sin(x) which have divergent non-infinite integrals, I'm just saying it can't happen for a probability distribution.
Does the integral of X over the real line exist?
Well it's zero!
So why shouldn't it exist
We're talking about a definite integral here. A symmetric bound function's integral .. no, that doesn't quite work.
16:24
@0celo7 Yes. The integrals of $x$ and $f(x)$ exist, separatey. But that doesn't mean the integral of $xf(x)$ exists.
@ACuriousMind what the hell
That makes zero sense
The integrable functions are not closed under multiplication, and the Cauchy distribution is an example of that.
@0celo7 He's right about that part.
But the integral of x doesn't exist.
I disagree, the integral is obviously zero
@0celo7 Well, prove it.
16:25
@0celo7 Only if the x itself is symmetrical.
@ACuriousMind It's odd!
@0celo7 And other conditions apply.
@0celo7 What's the integral of sin(x)
Being integrable is like being guilty: Things are non-integrable (innocent) until proven otherwise
It's odd too
@0celo7 The theorem you're trying to use has "the integral exists" as a prerequisite.
16:26
Yes, you can re-arrange how you integrate if you know the integral converges.
Then the positives and the negatives would cancel out.
It's like that resummation theorem - if a series converges absolutely, you can reorder the summands however you like. However, if the series doesn't converge, then different orderings will give different "results".
classica example is the 1+2-3+4-5 ...
@barrycarter zero
The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as the Lorentz distribution (after Hendrik Lorentz), Cauchy–Lorentz distribution, Lorentz(ian) function, or Breit–Wigner distribution. The Cauchy distribution is often used in statistics as the canonical example of a "pathological" distribution since both its mean and its variance are undefined. (But see the section Explanation of undefined moments below.) The Cauchy distribution does not have finite moments of order greater than or equal to one; onl...
I was going for a subsection link.
@ACuriousMind No. Do the symmetric integral from -L to L and take the limit.
16:29
Mind is still blown It still puzzles me why this thing has such a nice shape
@0celo7 Do that for sin(x)
@0celo7 Ah, but that is not how the improper integral at both ends is defined!
@Secret No, there are other examples where like 1 + -1 + 1 + -1 + 1 where combining pairs of terms converges, but the series as a whole does not.
@barrycarter 0
You have $\int_{-\infty}^\infty = \lim_{a\to -\infty}\lim_{b\to\infty}\int_a^b$, not $\int_{-\infty}^\infty = \lim_{a\to \infty}\int_{-a}^a$.
16:30
@ACuriousMind do you have to take the limits separately
@0celo7 And do you actually believe the definite integral of sin(x) from -Infinity to +Infinity really is 0?
@barrycarter yes
@0celo7 Yes, and it has to be independent of order.
@ACuriousMind well that's a shitty rule
@0celo7 But it's not. It jumps between -1 and +1
16:31
@barrycarter Proof?
@barrycarter This is why I like pathological mathematical objects, it really TEST one's understanding of the subject by stretching one's limit way way beyond the confines of intuition, (and I sort of believe that helps out of the box thinking)
@0celo7 Well, integrate sin(x) from 0 to L as L goes to infinity.
the problem is that there is no algorithm that can list them all out, which is why I often have trouble trying to study them because I don't even know their names
@0celo7 No, it's a necessary rule, otherwise you do not have that a function that is integrable on $X$ is integrable on every subset. E.g. the Cauchy distribution would be integrable on $\mathbb{R}$, but not on $\mathbb{R}_{\geq 0}$.
@Secret I like them because I'm pathological myself :)
16:32
@ACuriousMind what
Oh
Well I see nothing wrong with that.
really? :P
You could argue that the Cauchy distribution doesn't quite work because you can still predict its median and mode.
That's a possible extension, but my original question have not though that far. It is nice to know about that
which in that case, it will be either David's answer or your suggestion on the negation of axiom of choice
@ACuriousMind I see nothing wrong with it.
@0celo7 You see nothing wrong with a function that is integrable on $(a,b)$ not being integrable on $(0,b)$, where $a<0$?
(intentionally didn't put that link by itself so I can get a subsection link)
You started this because you wanted to use a nice property of integration (integrals of odd functions are zero). But this would destroy an even more basic property, namely $\int^a_b = \int_b^c + \int_c^a$.
@barrycarter (thoughts) Lp spaces are weird, where simple looking functions get pathological very quickly
Sadly, I don't know what an Lp space is.
16:37
@ACuriousMind Of course, but that's not what I'm suggesting.
@0celo7 Okay, what are you suggesting?
I'm talking about integrals over infinite sets
You're talking about integrals over sets with compact closure.
I agree that's a good rule for such integrals.
@0celo7 If I want to integrate sin(x) can I integrate from 0,Pi and then Pi,2*Pi, and then 2*Pi,3*Pi and so on?
@0celo7 You have to define the improper integral in the same way for both. Saying "take the limits separately, except when the limit point is $\infty$, then take only one symmetric limit" is just inconcsistent.
@barrycarter sine is odd and its integral is 0
End of discussion
16:40
and back home
@ACuriousMind Inconsistent? I think it's the only reasonable thing to do.
Are you serious?
@ slereah you missed a great detail of juicy pathologicalness, lol
Yes.
I don't see where it goes wrong
$\lim_{a\to\infty} \int_{-a}^a = \lim_{a\to\infty} \left(\int_{-a}^b + \int_b^{-b} + \int_{-b}^a \right)$.
16:42
@Acuriousmind another question (should be much easier to understand) Wikipedia said that conservation of probability is an exact conservation law due to symmetry. Is the symmetry U(1)?
@0celo7 LOL. "end of discussion" means you're conceding you're wrong :)
Well, I guess that now it's time to prove things about the reps of the Lorentz group
@barrycarter No.
Someone should go back to the definition of an integral from -Infinity to +Infinity to show engineer boy the error of his ways :)
It means I'm in class.
16:44
@0celo7 Oh, so those were two separate statements?
@barrycarter no.
@Secret Yes
@0celo7 You seem very negative today.
I'm still annoyed about the Cauchy distribution. It.. must... have.. a ... mean.
16:46
I am still puzzle why it has such a NICE shape, lol
there's plenty of distributions with no means
@0celo7 Here's where it goes wrong: If you define $\int_{-\infty}^\infty$ by the symmetric limit, you cannot write $\int_{-\infty}^b + \int_b^{-b} + \int_{-b}^\infty$ for some $b$, yet $\int_{U\cup V} = \int_U + \int_V$ is, for disjoint $U,V$, a basic property of any integral.
Women have a nice shape too, and no one understands them.
Just look at the Saint Petersburg distribution~
@Slereah But usually because the mean is infinite, right?
@Secret I see a flaw in your question. In order to choose numbers from a distribution, you must already have a method of choosing random numbers, right?
Also, even though the Cauchy distribution doesn't have a mean, it still has a PDF.
16:50
Well it's more like what David said: I do a series of experiments, and I get no long term % sucess that is a well defined number

I am not sure if that implies I have implicitly chosen random numbers in the process
and yes
@barrycarter I'm having life problems
@0celo7 You know the solution to that.
Mass shooting?
@0
@0celo7 Just requires one shooting cowboy :)
@Secret In order to choose a number from a distribution, I think you need an existing random number.
@Secret Also, the Cauchy thing doesn't work for a binary experiment.
I think @ACuriousMind deflected the issue. Cauchy still has a PDF.
@barrycarter Well, what the hell are you looking for, then? Probability theory is usually defined by PDFs, what is a "random process" if not one given by a probability distribution?
16:55
@ACuriousMind It may not exist, but: can you fill a bag in such a way that no one, not even you, can predict anything about what the output of choosing things from that bag will be?
Sure. Put on a blindfold.
@ACuriousMind With Cauchy, you can't predict the mean, but you can predict the shape of the PDF.
@ACuriousMind sdafaosj
@ACuriousMind Oh, you meant in order to choose the input to the bag.
@barrycarter what
@0celo7 Not a MASS shooting... unless you're talking about your own mass...
@ACuriousMind I disagree with your assertion. It's obvious what the mean of the Cauchy distribution is
16:56
@ACuriousMind Well, this gets a little philosophical then. Blindfold or not, how do you choose which things to put in the bag? Describe your process?
So anything you say that disagrees must be wrong.
@0celo7 Sadly, I have to agree with @ACuriousMind .. and I hate doing that, so please stop being wrong so much.
@0celo7 You claimed you were serious, and now you are saying something like that?
That's not even a complete sentence!
@barrycarter Well, that thing with the blindfold wasn't a serious suggestion. I don't think what you're looking for exists.

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