Lindo!

In probability theory there is a very clever trick for handling a problem that becomes too difficult. We just solve it anyway by:

1. making it still harder;
2. redefining what we mean by ‘solving’ it, so that it becomes something we can do;
3. inventing a dignified and technical-sounding word to describe this procedure, which has the psychological effect of concealing the real nature of what we have done, and making it appear respectable.

In the case of sampling with replacement, we apply this strategy as follows.

1. Suppose that, after tossing the ball in, we shake up the urn. However complicated the problem was initially, it now becomes many orders of magnitude more complicated, because the solution now depends on every detail of the precise way we shake it, in addition to all the factors mentioned above.
2. We now assert that the shaking has somehow made all these details irrelevant, so that the problem reverts back to the simple one where the Bernoulli urn rule applies.
3. We invent the dignified-soundingword randomization to describe what we have done. This term is, evidently, a euphemism, whose real meaning is: deliberately throwing away relevant information when it becomes too complicated for us to handle.

We have described this procedure in laconic terms, because an antidote is needed for the impression created by some writers on probability theory, who attach a kind of mystical significance to it. For some, declaring a problem to be ‘randomized’ is an incantation with the same purpose and effect as those uttered by an exorcist to drive out evil spirits; i.e. it cleanses their subsequent calculations and renders them immune to criticism.We agnostics often envy the True Believer, who thus acquires so easily that sense of security which is forever denied to us.

However, in defense of this procedure, we have to admit that it often leads to a useful approximation to the correct solution; i.e. the complicated details, while undeniably relevant in principle, might nevertheless have little numerical effect on the answers to certain particularly simple questions, such as the probability for drawing r red balls in n trials when n is sufficiently small. But from the standpoint of principle, an element of vagueness necessarily enters at this point; for, while we may feel intuitively that this leads to a good approximation, we have no proof of this, much less a reliable estimate of the accuracy of the approximation, which presumably improves with more shaking. The vagueness is evident particularly in the fact that different people have widely divergent views about how much shaking is required to justify step (2). Witness the minor furor surrounding a US Government-sponsored and nationally televized game of chance some years ago, when someone objected that the procedure for drawing numbers from a fish bowl to determine the order of call-up of young men for Military Service was ‘unfair’ because the bowl hadn’t been shaken enough to make the drawing ‘truly random’, whatever that means. Yet if anyone had asked the objector: ‘To whom is it unfair?’ he could not have given any answer except, ‘To those whose numbers are on top; I don’t know who they are.’ But after any amount of further shaking, this will still be true! So what does the shaking accomplish?

Shaking does not make the result ‘random’, because that term is basically meaningless as an attribute of the real world; it has no clear definition applicable in the real world. The belief that ‘randomness’ is some kind of real property existing in Nature is a form of the mind projection fallacy which says, in effect, ‘I don’t know the detailed causes – therefore – Nature does not know them.’ What shaking accomplishes is very different. It does not affect Nature’s workings in any way; it only ensures that no human is able to exert any wilful influence on the result. Therefore, nobody can be charged with ‘fixing’ the outcome.

At this point, you may accuse us of nitpicking, because you know that after all this sermonizing, we are just going to go ahead and use the randomized solution like everybody else does. Note, however, that our objection is not to the procedure itself, provided that we acknowledge honestly what we are doing; i.e. instead of solving the real problem, we are making a practical compromise and being, of necessity, content with an approximate solution. That is something we have to do in all areas of applied mathematics, and there is no reason to expect probability theory to be any different. E.T. Jaynes, Probability Theory, The Logic of Science