A simulation is only as reliable as its underlying mathematical assumptions. 4.1 Input Modeling and Distribution Fitting

Periods of inactivity between events are skipped entirely, maximizing computational efficiency. 4. Mathematical Modeling and Continuous Simulation

Kolmogorov-Smirnov (K-S) Test : Ideal for continuous distributions with smaller sample sizes. Critical Distributions Reference Table Distribution Common Application in Simulation Inter-arrival times of independent, memoryless events. Normal

Slide 28 — Tips for Building a Lecture PPT

: Collecting empirical data, identifying boundaries, and defining assumptions.

: The high-stakes gamble using random sampling to predict the future.

A classic algorithm utilizing the recursive formula:

Primary Use Cases: Infectious disease spreads, consumer market behaviors, and pedestrian evacuation dynamics. System Dynamics (SD)

: Gather empirical observations from the physical system.

Code debugging, structured walkthroughs, trace prints of entity pathways, and checking conservation laws (e.g., ensuring material entering a system equals material exiting). Validation: "Did we build the right model?"