onsider then two familiar games: coin tossing and playing dice, which I am going to use as examples. Coin tossing The coin has two sides, heads and tails. The experiment of tossing the coin has two possible outcomes (heads or tails), if we discard any possibility that the coin rolls on the floor and stops on its edge, as a third physical outcome! To be sure, the coin's mass is also assumed to be uniformly distributed into both sides, and the coin randomly flipped, in such a way that no side is more likely to show up than the other. The two outcomes are said to be equiprobable. The event space is S = {heads, tails}, and, according to the previous assumptions, p(heads) = p(tails). Since the space includes all possibilities, we apply the rule in Eq. (1.3) to get p(heads) = p(tails) = 1/2 = 0.5. The odds of getting heads or tails are 50%. In contrast, a realistic coin mass distribution and coin flip may not be SO perfect, SO that, for instance, p(heads) = 0.55 and p(tails) = 0.45. Rolling dice (game 1) Play first with a single die. The die has six faces numbered one to six (after their number of spots). As for the coin, the die is supposed to land on one face, excluding the possibility (however well observed in real life!) that it may stop on one of its eight corners after stopping against an obstacle. Thus the event space is S = {1, 2, 3, 4, 5, 6}, and with the equiprobability assumption, we have p(1) = p(2) = 0.166 666 6. Rolling dice (game 2) Now play with two dice. The game consists in adding the spots showing in the faces. Taking successive turns between different players, the winner is the one who gets the highest count. The sum of points varies between 1 + 1 = 2 to 6 + 6 = 12, as illustrated in Fig. 1.1. The event space is thus S = {2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, corresponding to 36 possible outcomes. Here, the key difference from the two previous examples is that the events (sum of spots) are not equiprobable. It is, indeed, seen from the figure that there exist six possibilities of obtaining the number