shanecurran
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quote:
Originally posted by coaster
quote:
Originally posted by shanecurran
Their conclusion is that randomness is that which cannot be predicted by humans, which I think is a good definition.
That would be a great definition if it were only humans trying to guess. Unfortunately, random number generation is a key part of encryption/decryption algorithms, thus insufficient for the computer age. 
The natural phenomena mentioned .... sounds very interesting.
I am pretty sure they meant humans, with all the tools they can possibly use (including computers).
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Wed Apr 27, 2011 4:05 pm |
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coaster
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The distribution for rolling a pair of dice: the numerical result of die face 1 plus die face 2:
2 = 1+1
3 = 1+2, 2+1
4 = 1+3, 2+2, 3+1
5 = 1+4, 2+3, 3+2, 4+1
6 = 1+5, 2+4, 3+3, 4+2, 5+1
7 = 1+6, 2+5, 3+4, 4+3, 5+2, 6+1
8 = 2+6, 3+5, 4+4, 5+3, 6+2
9 = 3+6, 4+5, 5+4, 6+3
10 = 4+6, 5+5, 6+4
11 = 5+6, 6+5
12 = 6+6
the population of the distribution is 36, distributed as follows:
2 = 1 instance
3 = 2 instances
4 = 3 "
5 = 4 "
6 = 5 "
7 = 6 "
8 = 5 "
9 = 4 "
10 = 3 "
11 = 2 "
12 = 1 "
In an infinite series of rolls, the number of times a particular numerical value would be produced should equal its number of instances divided by the population, no? Then a 2 would be rolled 1/36 times and and 7 would be rolled 6/36 times; and the number of times that a 7 would appear in the series would be six times more than the number of times that a 1 would appear. It couldn't be predicted with 100% certainty what the next roll of the dice would produce, but it could be predicted that the probability of the next roll being a 7 is 17% (rounded) and the probability of rolling a 2 is only 3%. Therefore wouldn't a 2 be (roughly) six times more random than a 7? (If randomness is defined as predictability)
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Wed Apr 27, 2011 4:05 pm |
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shanecurran
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quote:
Originally posted by coaster
It couldn't be predicted with 100% certainty what the next roll of the dice would produce, but it could be predicted that the probability of the next roll being a 7 is 17% (rounded) and the probability of rolling a 2 is only 3%. Therefore wouldn't a 2 be (roughly) six times more random than a 7? (If randomness is defined as predictability)
Here in lies the problem with your made up definition of randomness and predictability (both of which are false). The 2 is just as predictable as the 7, it simply does not happen as often. The 7 is no more random than the 2.
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Mon May 09, 2011 7:14 pm |
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coaster
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Well, you could offer an authoritative proof if you're so sure I'm wrong. I'm not convinced just on your say so.
quote:
The 2 is just as predictable as the 7, it simply does not happen as often.
I'm using the term "predictability" as a synonym for "probability" and the mathematical definition of probability is:
"A number expressing the likelihood of the occurrence of a given event, especially a fraction expressing how many times the event will happen in a given number of tests or experiments"
(source: TheFreeDictionary)
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Tue May 10, 2011 6:55 am |
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shanecurran
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"Synonyms: predict, call, forecast, foretell, prognosticate
These verbs mean to tell about something in advance of its occurrence by means of special knowledge or inference: predict an eclipse; couldn't call the outcome of the game; forecasting the weather; foretold events that would happen; prognosticating a rebellion."
(source: TheFreeDictionary)
Think about this in terms of gambling. Lets say there are two games. In the first game you try to predict the flip of a coin, where the probability of heads = 1/2 and the prob of tails =1/2. The second game you try to predict which card will be drawn next in a 52 card deck. The probability of seeing each card is 1/52. If it is a fair bet on both games (where expected value equals zero, or you win $1 for a correct guess on the coin toss and $52 for a correct guess in the card shuffle). Both games are random. Are you saying that you can predict the coin toss better than the card shuffle and therefore will make more money in that game?
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Tue May 10, 2011 2:03 pm |
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shanecurran
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Another interesting relationship is between determinism and predictability. Determinism is a necessary but not sufficient condition for predictability. Something that is perfectly predictable must be deterministic, but something may still be deterministic even if one can not accurately predict the outcome.
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Tue May 10, 2011 2:18 pm |
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coaster
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quote:
Originally posted by shanecurran
Are you saying that you can predict the coin toss better than the card shuffle and therefore will make more money in that game?
No. I'm saying I can predict the coin toss with a probability of being right 50% of the time. I can predict the card with a probability of 2%. So I can predict the coin toss better than the card. But I cannot make more money in that game because you haven't accounted for loss. If you also assign $1 for each incorrect prediction in both games then the probability of losing a dollar is 50% in the coin toss and the probability of losing a dollar in the card draw is 98%.
Though that's just for the first card, because if you track which cards are removed from the deck then the probability of predicting the next card goes up with each card removed because the set of cards remaining decreases. The probability remains at 2% only if you have an infinite number of each card in the same proportion.
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Tue May 10, 2011 3:58 pm |
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nix.pollard77
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Overall i think he wants to build some interest.
But it can be interesting cannot be random.
school management software
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Fri May 13, 2011 1:43 pm |
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shanecurran
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quote:
Originally posted by nix.pollard77
Overall i think he wants to build some interest.
But it can be interesting cannot be random.
Can you explain what you mean by this statement?
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Fri May 13, 2011 3:10 pm |
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taylor66
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Don,t think so.
It does not looks to be random.
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Fri May 20, 2011 2:33 pm |
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