JesseM said:
billschnieder said:
I gave you an abstract list. No mention of anything such as trial. No mention of anything such a physical process. I asked you to give me the probability of one of the entries from the list, and you told me it was impossible despite the fact that this is what is done everyday in your favorite frequentist approach to probability.
Not if we are excluding "finite frequentism", which I already told you I was doing.
So you you are saying if you were not exclusing "finite frequentism" you will be able to give an answer? So, you are effectively picking and triming your definition of probability for argumentative purposes as more of your statements will show below. You are not being serious.
JesseM said:
Does your list of four give us enough information to know the frequency of ++ in the limit as the sample size goes to infinity?
Bah! This list is the entire context of the question! The list is the
population. True probability of the (++) in the list, is the relative frequency of (++) in the list. This is the frequentist approach, which you now want to abandon in order to stay afloat.
JesseM said:
billschnieder said:
When ever you say the probability of Heads and Tails is 0.5 you are doing it, whenever you say the probability of one face of a die is 1/6, you are doing the exact same thing you now claim is impossible. Go figure.
[bu]No, in those cases I am just using the physical symmetry of the object being flipped/rolled to make a theoretical prediction about what the limit frequency would be[/u], perhaps along with the knowledge that empirical tests do show each option occurs with about equal frequency in large samples
Hehe! Do you know of anybody who has ever performed an infinite number of coin or die tosses? I think not. So you can not know what the limit will be as the number of tosses tends toward infinity. And since you have continued to insist on your ridiculous idea that the "true probability" must be defined as the limit as the number of trials tends towards infinity, the above response is very telling.
Furthermore, did you really think I will not notice the fact that you have now abandoned your favorite frequentist approach and now you are using the bayesian approach (see underlined text above) to decide that the P(Heads) = 0.5. If you can use symmetry of the coin to decide that P(Heads) = 0.5, why couldn't you also use symmetry of my abstract list to decide that P(++) is 1/4?? I'm sure if I looked, I will not need to look hard to find a post in which you wrote a list not very different from mine and also wrote P(++) to be 1/4 or similar, without having performed an infinite number of damned "trials". So as I mentioned earlier, you are not being serious, just finding anything you can hang-on to, even if it means contradicting yourself.
JesseM said:
billschnieder said:
I already gave you the answer which is 1/4.
Yes, and that answer is incorrect if we are talking about the "limit frequentist probability", as I already made clear I was doing.
You say it is impossible to calculate an answer, then when I give you the answer, you then say the answer is wrong. How do you know it is wrong, if you are unable to calculate the correct one? You are way off base, and the answer is correct in ANY probabilistic approach.
The relative frequency of (++) in my list is 1/4. Since my list is the population, P(++)=1/4 you do not need any trials to determine this.
JesseM said:
JesseM said:
Note that the wikipedia article says "close to the expected value", not "exactly equal to the expected value".
JesseM said:
An "expectation value" like E(a,b) would be interpreted in frequentist terms as the expected average result in the limit as the number of trials (on a run with detector settings a,b) goes to infinity
Um, how do you figure? The two statements of mine are entirely compatible, obviously you are misunderstanding something here
It is quite clear from the two statements that if average from the law of large numbers is close to but not equal to the true expectation value, it can not be the definition of the expectation value! Which one is it? The definition of the expectation value can not at the same time be only approximately equal to it!?
JesseM said:
Yes, and with that context there isn't enough information to estimate the limit frequentist probability which is the only notion of probability I want to use
...
billschnieder said:
You can visualize it by thinking that if you would randomly pick an entry from the the list I gave you
Well, that's an entirely separate question, because then you are dealing with a process that can repeatedly pick entries "randomly" from the list for an arbitrarily large number of trials. But you didn't say anything about picking randomly from the list, you just presented a list of
results and asked what P(++) was.
It is not an entirely separate question. I did not mention any trials in my question. But you have stated that the only notion of probability you want to use is the "limit frequentist probability", even though initially you just said "frequentist", but if you want to stick to that limited approach, which is only interested in "trials", you could still have provided an answer to the question by imagining what the limit will be if you actually randomly picked items from my list. Is it your claim that this is also impossible?
Secondly, despite my repeated correction of your false statements that I presented "results" or "trials", you keep saying it. You quickly jumped to claim I never mentioned trials, yet in the next sentence, you say I presented "results", even though I never characterized the list as such, and corrected your attempts to characterize it as such multiple times! You are not being honest.