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Statistical regularity has motivated the development of the relative frequency concept of probability.
Most of the procedures commonly used to make statistical estimates or tests were developed by statisticians who used this concept exclusively. 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.
Since the 18th century, there has been a debate between frequentists and Bayesians. The former insisted that statistical procedures only made sense when one uses the relative frequency concept. The Bayesians supported the use of degrees of belief as a basis for statistical practice.
The frequentist position is the one you probably heard at school: perform an experiment lots of times, and measure the proportion where you get a positive result - this proportion, if you perform the experiment enough times, is the probability.
The problem comes in those cases where we haven't performed an experiment yet, or where there's no possible way an experiment could be performed - in these cases, frequentism can't help us. To solve this, Bayesians assume a hypothetic reference class from which random selection is made. The sunrise problem illustrates this.
See also probability interpretations -- Bayesian probability -- eclectic probability __ probability -- statistics -- statistical regularity __ probability axioms -- games of chance
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