Bayesianske

Bayesianske refers to anything related to Bayesian statistics or Bayesian inference. This is a statistical theory named after Thomas Bayes, an 18th-century British mathematician and theologian. Bayesian statistics provides a framework for updating probabilities based on new evidence. It is distinguished from frequentist statistics by its approach to probability itself.

In Bayesian statistics, probability is interpreted as a degree of belief rather than a long-run frequency. A core concept is Bayes' theorem, which describes how to update the probability of a hypothesis as more evidence or information becomes available. The theorem mathematically combines prior beliefs with observed data to produce a posterior probability. This posterior probability represents a revised belief after considering the new evidence.

Bayesian inference is the process of applying Bayes' theorem to make statistical inferences. It involves starting with a prior distribution representing initial beliefs about a parameter, then using observed data to compute a posterior distribution. This posterior distribution then summarizes the updated beliefs about the parameter. Applications of Bayesian methods are widespread, including in machine learning, artificial intelligence, medical diagnosis, and scientific research. The methods are valued for their ability to incorporate prior knowledge and their intuitive interpretation of probabilities as degrees of belief.