Random numbers

Question

While thinking about this question and conversing with the participants, the idea came up that shuffling a finite set of clearly biased random numbers makes them random because you don't know the order in which they were chosen. Is this true and if so can someone point to some resources?

EDIT: I thnk I might have been a little unclear. Suppose a bad random numbers generator. Take n values. These are biased(the rng is bad). Is there a way through shuffling to make the output of the rng over multiple trials statistically match the output of a known good rng?

Answer 1

False

The set is finite, suppose consists of n numbers. What happens if you choose n+1 numbers? Let's also consider a basic random function as implemented in many languages which gives you a random number in [0,1). However, this number is limited to three digits after the decimal giving you a set of 1000 possible numbers (0.000 - 0.999). However in most cases you will not need to use all these 1000 numbers so this amount of randomness is more than enough.

However for some uses, you will need a better random generator than this. So it all comes down to exactly how many random numbers you are going to need, and how random you need them to be.

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Addition after reading original question: in the case that you have some sort of limitation (such as in the original question in which each set of selected numbers must sum up to a certain N) you are not really selected random numbers per se, but rather choosing numbers in a random order from a given set (specifically, a permutation of numbers summing up to N).

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Addition to edit: Suppose your bad number generator generated the sequence (1,1,1,2,2,2). Does the permutation (1,2,2,1,1,2) satisfy your definition of random?

Answer 2

Just shuffling a set of numbers of already random numbers won't do anything to the probability distribution of course. That would mean false. Perhaps I misunderstand your question though?

Answer 3

I would say false, with a caveat:

I think there is random, and then there is 'random-enough'. For most applications that I have needed to work on, 'random-enough' was more than enough, i.e. picking a 'random' ad to display on a page from a list of 300 or so that have paid to be placed on that site.

I am sure a mathematician could prove my very basic 'random' selection criteria is not truly random at all, but in fact is predictable - for my clients, and for the users, nobody cares.

On the other hand if I was writing a video game to be used in Las Vegas where large amounts of money was at hand I'd define random differently (and may have a hard time coming up with truly random).

Answer 4

It's not true. In the other question the problem is to select 30 random numbers in [1..9] with a sum of 200. After choosing about on average 20 of them randomly, you reach a point where you can't select nines anymore because this would make the total sum go over 200. Of the remaining 10 numbers, most will be ones and twos. So in the end, ones and twos are very overrepresented in the selected numbers. Shuffling doesn't change that. But it's not clear how the random distribution really should look like, so one could say this is as good a solution as any.

In general, if your "random" numbers will be biased to, say, low numbers, they will be biased that way no matter the ordering.

Answer 5

False.

There is an easy test: Assume the bias in the original set creation algorithm is "creates sets whose arithmetic average is significantly lower than expected average". Obviously, shuffling the result of the algorithm will not change the averages and thus not remove the bias.

Also, regarding your clarification: How would you shuffle the set? Using the same bad output from the bad RNG that created the set in the first place? Or using a better RNG? Which raises the question why you don't use that directly.

Answer 6

Completely and utterly untrue: Shuffling doesn't remove a bias, it just conceals it from the casual observer. It's like removing your dog's fondly-laid present from your carpet by just pushing under the sofa - you really haven't solved the problem, you've just made it less conspicuous. Anyone with a nose knows that there is still a problem that needs removing.

The randomness must be applied evenly over the whole range, so here's one way (off the top of my head, lots of assumptions, yadda yadda. The point is the approach, not the code - start with everything even, then introduce your randomness in a consistent fashion until you're done. The only bias now is dependent on the values chosen for 'target' and 'numberofnumbers', which is part of the question.)

target = 200
numberofnumbers = 30
numbers = array();
for (i=0; i<numberofnumbers; i++)
  numbers[i] = 9
while (sum(numbers)>target)
  numbers[random(numberofnumbers)]--