Ney

The Ney, or Neyman–Pearson, framework is a statistical method used to make decisions between two competing hypotheses—like testing whether a new drug is effective or not. It focuses on controlling the probability of incorrect conclusions (errors), specifically minimizing false positives (Type I errors) while maintaining a desired power to detect true effects (true positives). This approach helps researchers set clear criteria (thresholds) for accepting one hypothesis over another, ensuring decisions are made systematically and with a known level of confidence. It's widely used in scientific studies, quality control, and other fields requiring rigorous hypothesis testing.