Trials: In simulation, trials refer to the number of times we repeat an experiment or scenario. Each trial represents one iteration of the simulation and helps us gather data on different outcomes.
Probabilities: Simulation often involves calculating probabilities, which represent the likelihood of certain events occurring. These probabilities are based on observed frequencies from multiple trials and help us make predictions about real-world scenarios.
Randomness: Simulations rely on randomness to mimic real-life uncertainty. By introducing random elements into our models, we can simulate unpredictable events and account for variability in outcomes.