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Many Bayesian methods required a lot of computation to complete, and most methods that were widely used during the century were based on the frequentist interpretation.However, with the advent of powerful computers and new algorithms like Markov chain Monte Carlo, Bayesian methods have seen increasing use within statistics in the 21st century.Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event.

For example, a coin can be represented as samples from a Bernoulli distribution, which models two possible outcomes.

The Bernoulli distribution has a single parameter equal to the probability of one outcome, which in most cases is the probability of landing on heads.

Devising a good model for the data is central in Bayesian inference.

Many Bayesian methods were developed by later authors, but the term was not commonly used to describe such methods until the 1950s.

During much of the 20th century, Bayesian methods were viewed unfavorably by many statisticians due to philosophical and practical considerations.

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