Gargiulo (Gargiulo’s Prior)

Gargiulo's Prior, in Bayesian statistics, refers to a way of expressing initial beliefs about a parameter before seeing new data. It involves using historical information or expert knowledge to define a starting point, which is then updated as new evidence becomes available. This prior helps improve the accuracy of predictions or estimates by incorporating existing understanding, making the analysis more informed and reliable. Essentially, it’s a baseline belief that guides how we interpret new information within a statistical framework.