I shall begin with that of the roulette. I have said that the point where the needle will stop depends upon the initial push given it. What is the probability of this push having this or that value? I know nothing about it, but it is difficult for me not to suppose that this probability is represented by a continuous analytic function. The probability that the push is comprised between α and α + ε will then be sensibly equal to the probability of its being comprised between α + ε and α + 2ε, provided ε be very small. This is a property common to all analytic functions. Minute variations of the function are proportional to minute variations of the variable.
But we have assumed that an exceedingly slight variation of the push suffices to change the color of the sector over which the needle finally stops. From α to α + ε it is red, from α + ε to α + 2ε it is black; the probability of each red sector is therefore the same as of the following black, and consequently the total probability of red equals the total probability of black.
The datum of the question is the analytic function representing the probability of a particular initial push. But the theorem remains true whatever be this datum, since it depends upon a property common to all analytic functions. From this it follows finally that we no longer need the datum.
What we have just said for the case of the roulette applies also to the example of the minor planets. The zodiac may be regarded as an immense roulette on which have been tossed many little balls with different initial impulses varying according to some law. Their present distribution is uniform and independent of this law, for the same reason as in the preceding case. Thus we see why phenomena obey the laws of chance when slight differences in the causes suffice to bring on great differences in the effects. The probabilities of these slight differences may then be regarded as proportional to these differences themselves, just because these differences are minute, and the infinitesimal increments of a continuous function are proportional to those of the variable.
Take an entirely different example, where intervenes especially the complexity of the causes. Suppose a player shuffles a pack of cards. At each shuffle he changes the order of the cards, and he may change them in many ways. To simplify the exposition, consider only three cards. The cards which before the shuffle occupied respectively the places 123, may after the shuffle occupy the places
123, 231, 312, 321, 132, 213.
Each of these six hypotheses is possible and they have respectively for probabilities:
p1, p2, p3, p4, p5, p6.
The sum of these six numbers equals 1; but this is all we know of them; these six probabilities depend naturally upon the habits of the player which we do not know.
At the second shuffle and the following, this will recommence, and under the same conditions; I mean that p4 for example represents always the probability that the three cards which occupied after the nth shuffle and before the n + 1th the places 123, occupy the places 321 after the n + 1th shuffle. And this remains true whatever be the number n, since the habits of the player and his way of shuffling remain the same.