Algorithmization of the Evaluation of Decisions by the Neumann-Pearson Criterion

As a result of research, a methodology for determining Bayesian risk was developed when testing statistical hypotheses in the problem of evaluating the effectiveness of managerial decisions by the Neumann-Pearson criterion. A scientific result was obtained in the work, which made it possible to determine virtual a priori probabilities corresponding to a given probability of an error of the first kind (false alarm), and a rule was established for determining the threshold for comparing sufficient statistics from simulation results.