Priors

Priors are initial assumptions or beliefs about a particular situation or data, formed before seeing new information. In data analysis or statistics, they represent what we think we know beforehand about a parameter or outcome. As new evidence becomes available, these priors are updated to form a revised understanding, called a posterior. Priors help incorporate existing knowledge into the analysis, making predictions or decisions more informed and contextually grounded. They are a foundational concept in Bayesian reasoning, balancing previous insights with new data to improve accuracy and understanding.