Frequentist Inference without Repeated Sampling

Abstract

Frequentist inference typically is described in terms of hypothetical repeated sampling but there are advantages to an interpretation that uses a single random sample. Contemporary examples are given that indicate probabilities for random phenomena are interpreted as classical probabilities, and this interpretation is applied to statistical inference using urn models. Both classical and limiting relative frequency interpretations can be used to communicate statistical inference, and the effectiveness of each is discussed. Recent descriptions of p-values, confidence intervals, and power are viewed through the lens of classical probability based on a single random sample from the population.