Likelihood

Early developments of probability as a mathematical discipline came as a response to questions about games of chance played repeatedly. The mathematical formulation owes much to the work of Pierre de Fermat and Blaise Pascal in the seventeenth century. The game is described in terms of a well defined trial (a play); the result of any trial is one of a specific set of distinguishable outcomes. Although the result of any play is not predictable, certain “statistical regularities” of results are observed. In classical probability, the possible results are described in ways that make each result seem equally likely. If there are N such possible “equally likely” results, each is assigned a probability 1/N.The developers of mathematical probability also took cues from early work on the analysis of statistical data. To apply these results, one considers the selection of a member of the population on a chance basis. One then assigns the probability that such a person will have a given condition. The trial here is the selection of a person, but the interest is in the condition. Out of this statistical formulation came an interest not only in probabilities as fractions or relative frequencies but also in averages or expectatons. These averages play an essential role in modern probability. This approach avoided the "equally likely" limitation of classical probability.Inherent in informal thought, as well as in precise analysis, is the notion of an event to which a probability may be assigned as a measure of the likelihood the event will occur will occur on any trial. A successful mathematical model must formulate these notions with precision. The event corresponding to some characteristic of the possible outcomes is the set of those outcomes having this characteristic. The event occurs if and only if the outcome of the trial is a member of that set (i.e., has the characteristic determining the event).