Abstract

There are fundamental differences between real]world and computer simulation experiments. In simulations, an experimenter has full control over everything ] time, uncertainty, causality, structure, environment, etc. This talk demonstrates how synergies in simulation experiments, models, codes, and analysis sometimes make these indistinguishable. This motivates us to revise two famous quotes about statistical modeling and experimental design in the simulation context. George E. P. Box, one of the most prolific statisticians in recent history, is attributed with the quote gAll models are wrong; some are usefulh. A simulation model and experiment that is designed for a specific analytical purpose may be both more wrong and more useful. Sir R. A. Fisher, credited as the creator of statistical experimental design, is often quoted as saying, gThe best time to design an experiment is after youfve run it.h The best time to design a simulation model and experiment is often while youfre running it. Examples are presented where analysis]specific simulations and simulation]specific experiments have greatly improved the production and distribution of life]saving biopharmaceuticals. However, the methods apply more generally to production and service systems.