In this lecture, we continue our discussion of the use of performance estimation strategies for absolute performance (particularly in the case of transient simulation models of terminating systems). We review the sources of variation within and across replications in a simulation study, followed by a definition of common point estimators (for mean as well as quantile estimation), and then we define measures of estimator variance (e.g., standard error of the mean, SEM). That allows us to introduce interval estimation, particularly confidence interval estimation, which represents the interval of hypotheses that would fail to be rejected by a one-sample t-test. We discuss interval estimation in terms of quantile estimation as well. Finally, we conclude with a method of using constraints on interval half width to guide how many simulation replications are needed for a given simulation study.
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