In this lecture, we review hand-simulation/DES simulation basics. We then introduce how to simulate discrete event system simulations (which are dynamic simulation models built around the idea of "state") in declarative programming frameworks like spreadsheets (which have no "state"). We work through the relationships necessary to encode in a spreadsheet to simulate a single-channel, single-server queue. We then pivot to covering comments from Lab 2, which was a hand simulation of a system with partial batching. This allows for motivating why we use multiple replications when we do empirical work with stochastic simulations, and how tools such as common random numbers can reduce variance but require special statistical tools (such as the paired-difference t-test). We then discuss the multiple comparisons problem, some ways to solve it, and how linear models extend what we can say from empirical studies -- so we can go from statistically significant to practically significant. (i.e., we can better characterize the "effect size" of a variable we have control over).