In this lecture, we continue the introduction to Discrete Event System (DES) simulation fundamentals. This includes revisiting the differences between entities, attributes, resources, state vectors, and output metrics. We discuss how "stochastic" modeling uses randomness to simplify building simulation models by substituting fine-grained deterministic details with random characterizations that have similar variability. With this in mind, we describe activities as the "inputs" to systems (and "input modeling" as a process of choosing the right probabilistic distributions for those inputs) and delays as the "outputs" of systems. Performance measures aggregate over the outputs of many simulation runs, which are required because each simulation run has a variable output. We close the lecture with an introduction to the event-scheduling world view, where simulations move from event to event, using logic at each event to schedule new events in the future on the "event calendar."