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Probability, statistics, and experimentation are fundamental concepts in simulation that work together to model and analyze real-world systems under uncertainty. Probability provides a mathematical framework for describing random events and predicting the likelihood of different outcomes, while statistics involves collecting, analyzing, and interpreting data generated from simulations to draw meaningful conclusions. Experimentation in simulation refers to designing and running multiple simulation scenarios under varying conditions to observe system behavior, test hypotheses, and evaluate performance. Together, these elements enable decision-makers to understand complex systems, estimate risks, optimize processes, and make informed choices based on simulated evidence rather than relying solely on theoretical assumptions or real-world trials.
This lecture is part of CSC318 MODELING AND SIMULATION in the Computer Science department. The course has 15 recorded lectures across 5 series, all free to watch.