Frequency probability
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 Frequency probability is the interpretation of probability that defines an event's probability as the limit of its relative frequency in a large number of trials. The problems and paradoxes of the classical interpretation motivated the development of the relative frequency concept of probability. Most of the mathematics commonly used to make statistical estimates or tests are developed by statisticians who subscribe to this view of probability. They are usually called frequentists, and their position is called frequentism. This school is often associated with the names of Jerzy Neyman and Egon Pearson who described the logic of statistical hypothesis testing. Other influential figures of the frequentist school include John Venn, R.A. Fisher, and Richard von Mises.
DefinitionFrequentists talk about probabilities only when dealing with well-defined random experiments. The set of all possible outcomes of a random experiment is called the sample space of the experiment. An event is defined as a particular subset of the sample space that you want to consider. For any event only one of two possibilities can happen; it occurs or it does not occur. The relative frequency of occurrence of an event, in a number of repetitions of the experiment, is a measure of the probability of that event. ScopeThis is a highly technical and scientific definition and doesn't claim to capture all connotations of the concept 'probable' in colloquial speech of natural languages. Compare how the concept of force is used by physicists in a precise manner despite the fact that force is also a concept in many natural languages, used in religious texts for example. However, this seldom causes problem or confusion, as the context usually reveals if it's the scientific concept that is intended or not. As William Feller noted:
EtymologyAccording to the Oxford English Dictionary, the term 'frequentist' was first used by M. G. Kendall [1] in 1949, who observed
and went on to say
Alternative viewsBayesianismThe main alternative view, Bayesianism is more popular among decision theorists. Frequentists can't assign probabilities to things outside the scope of their definition. In particular, frequentists attribute probabilities only to events while Bayesians apply probabilities to arbitrary statements. For example, if one were to attribute a probability of 1/2 to the proposition that "there was life on Mars a billion years ago" one would violate frequentist canons, because neither an experiment nor a sample space is defined here. However, such degree-of-belief assignments of probability to statements are the basis of Bayesian probability theory. See also
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