![]() In essence, one needs to first estimate the size of the set of all possible outcomes of the dice throw known as the sample space, and then figure out how many of these result in the desired sum. A series of fair dice rolls can be modelled as independent events. Also, the outcome of each roll is independent of rolls preceding or succeeding it. ![]() The dice are assumed to be fair (unbiased), meaning each side has equal probability of turning up. The question is: what is the probability of rolling a given sum with two six-sided dice?. ![]() The image above shows six such dice each with a different face up. One throws two dice and the value of a roll is whatever number faces up once the die settles in place. Each die is a cube with six faces with the numbers from one to six printed on each side. In this example, two dice are thrown together and one records their face values, and computes their sum. The classic case of exploring dice throw probabilities (dice rolling odds) is to estimate the chance of landing a given sum on the faces of two six-sided dice. With such versatility you can calculate dice probabilities for most games of chance such as Craps, Backgammon, Dungeons & Dragons (D&D), Balut, Dice 10000, Diceball!, Dudo, Elder Sign, Kismet, Yahtzee, Bunco, and many more.
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