I can't seem to get my head around a simple issue of judging probability. Perhaps someone here can point to an obvious flaw in my thinking.
Let's say we have a binary generator, a machine that outputs a required sequence of ones and zeros according to some internally encapsulated rule (deterministic or probabilistic). All binary generators look alike and you can only infer (a probability of) a rule by looking at its output.
You have two binary generators: A and B. One of these is a true random generator (fair coin tosser). The other one is a biased random generator: stateless (each digit is independently calculated from those given before), with probability of outputting zero p(0) somewhere between zero and one, but NOT 0.5 - let's say it's uniformly distributed in the range [0; .5) U (.5; 1]. At this point, chances that A is a true random generator are 50%.
Now you read the output of first ten digits generated by these machines. Machine A outputs 0000000000. Machine B outputs 0010111101. Knowing this, is the probability of machine A being a true random generator now less than 50%?
My intuition says yes.
But the probability that a true random generator will output 0000000000 should be the same as the probability that it will output 0010111101, because all sequences of equal length are equally likely. The biased random generator is also just as likely to output 0000000000 as it is 0010111101.
So there seems to be no reason to think that a machine outputting a sequence of zeros of any size is any more likely to be a biased stateless random generator than it is to be a true random generator.
I know that you can never know that the generator is truly random. But surely you can statistically discern between random and non-random generators?
With a fair random generator:
p(0000000000) = 1/2^10
p(1000000000) = 1/2^10
p(0100000000) = 1/2^10
p(0010000000) = 1/2^10
The numbers produced are independent of each other and for our purposes we don't care about the order. The relevant thing is how likely it is is to produce a given total number of zeroes or ones.
p(just one 1) = 10/2^10; A whole heap more likely!
So the chance that the generator is fair is rather slim. You can calculate just how slim by simply applying bayes rule (and doing some integration).
On a related note if you role two six sided dice you are just as likely to get two sixes as you are to get a three and a five. But if you are playing Settlers of Catan and put all your settlements next to the twelve instead of the eight then you are probably going to lose.
Actually p(just one 1) = 10/(2^10).
Nitpick: this is true if by "a three and a five" you mean (that the dice are labeled and) "die A comes up 3, and die B comes up 5", but it's false as written (and in games like Settlers, the identities of simultaneously thrown dice are not tracked).