frequentistlik

Frequentistlik is a framework for statistical inference that defines probability as the long-run frequency of an event. In this view, probabilities are objective properties of repeatable events. For example, when a fair coin is tossed, the probability of heads is 0.5 because in an infinitely long sequence of tosses, approximately half will be heads.

Frequentist methods focus on the properties of statistical procedures over many hypothetical repetitions of an experiment or data collection process. This means that a confidence interval, for instance, is interpreted as a procedure that, if repeated many times, would capture the true population parameter a certain percentage of the time (e.g., 95%). It does not make a statement about the probability of the specific interval containing the true parameter after it has been calculated.

Key concepts in frequentist statistics include hypothesis testing, p-values, and confidence intervals. Hypothesis testing involves setting up a null hypothesis and an alternative hypothesis, and then using data to determine if there is enough evidence to reject the null hypothesis. The p-value quantifies the probability of observing data as extreme as, or more extreme than, the observed data, assuming the null hypothesis is true.

Frequentist inference is widely used in many scientific disciplines due to its objective interpretation and well-established methodologies. It contrasts with Bayesian inference, which treats probability as a measure of subjective belief and allows for the incorporation of prior knowledge.