What is Bayes Theorem?
Bayes’ theorem, sometimes called Bayes’ rule or the principle of inverse probability, is a mathematical theorem that follows very quickly from the axioms of probability theory. In practice, it is used to calculate the updated probability of some target phenomenon or hypothesis H given new empirical data X and some background information, or prior probability. The prior probability of some hypothesis is usually represented by some percentage between 0% and 100%, or some number between 0 and 1. This probability is often called degree of confidence, and is meant to vary from observer to observer, as not all observers have had the same experience and therefore cannot make equivalent probability estimates for any given hypothesis. The application of Bayes’ theorem in a scientific context is called Bayesian inference, which is a quantitative formalization of the scientific method. It allows the optimal revision of theoretical probability distributions given experimental results. Bayes’ theor
Bayes’ theorem, sometimes called Bayes’ rule or the principle of inverse probability, is a mathematical theorem that follows very quickly from the axioms of probability theory. In practice, it is used to calculate the updated probability of some target phenomenon or hypothesis H given new empirical data X and some background information, or prior probability. The prior probability of some hypothesis is usually represented by some percentage between 0% and 100%, or some number between 0 and 1. This probability is often called degree of confidence, and is meant to vary from observer to observer, as not all observers have had the same experience and therefore cannot make equivalent probability estimates for any given hypothesis. The application of Bayes’ theorem in a scientific context is called Bayesian inference, which is a quantitative formalization of the scientific method. It allows the optimal revision of theoretical probability distributions given experimental results.
