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Discrete Model ✔✔Handles finite or countable data sets.\
Continuous Model ✔✔Handles continuous or uncountable data sets.
Stochastic Model ✔✔Incorporates randomness or probability in predictions.
Deterministic Model ✔✔Outcomes determined by fixed parameters.
Dynamic Model ✔✔Describes long-term relationships over time.
Static Model ✔✔Describes short-terms relationships, without time changes.
Monte Carlo Simulation ✔✔Uses random sampling for statistical analysis.
Discrete-Event Simulation ✔✔Models systems as events occurring at specific times.
Agent-Based Modeling ✔✔Simulates interactions of autonomous agents.
Manufacturing Simulation ✔✔Evaluates part movement and resource demand.
Throughput ✔✔Rate at which a system produces output.
Bottlenecks ✔✔Points of congestion limiting system performance.
Reliability ✔✔Probability of a system performing without failure.
Supply Chain (SC) ✔✔Network of nodes for product flow management.
Law of Averages ✔✔Overuse of averages leads to unrealistic results.
Sequential Hypothesis Tests ✔✔Tests to determine disease presence over time.
Predictive Analytics ✔✔Using data to anticipate future events.
Integration via Simulation ✔✔Estimating area under curves using random sampling.
Box Muller Method ✔✔Generating normal random variables from uniform ones.
MM1 Queue Simulation ✔✔Analyzing single-server queue dynamics.