Detection theory

Detection theory is a framework used to understand how we distinguish between what is signal (something present) and noise (background or random data). It analyzes decision-making under uncertainty, considering factors like the clarity of the signal, the cost of errors, and individual sensitivity. In practical terms, it explains why sometimes we miss detecting an important event or falsely think something is there when it isn't—like missing a faint alarm or hearing a false alarm. This theory applies in fields like medicine, radar, and psychology, helping optimize detection strategies and interpret how humans or systems make critical decisions amid uncertainty.