A probabilistic model as used in classical physics and other sciences can be thought of as a triple \((\SC,\EC,\MC)\), a sample space \(\SC\), an event algebra \(\EC\) and a probability measure \(\MC\). When a die is rolled the sample space \(\SC\) consists of six mutually exclusive possibilities, one and only one of which actually occurs. The event algebra can be set equal to the collection of all \(2^6\) subsets of \(\SC\), including the empty set and \(\SC\) itself; it forms a Boolean algebra under complements and intersections. Finally, \(\MC\) assigns probabilities, real numbers between 0 and 1, to the different sets in \(\EC\) according to certain rules. Again we need only consider the simplest situation in which \(\SC\) is finite or countable, and a nonnegative number \(p_j\) is assigned to each \(j\in\SC\) in such a manner that \(\sum_j p_j = 1\). The probability for some \(E\in \EC\) is then given by the formula