Simulation Models Flashcards
7 cards from real APCSP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Simulation Models flashcards as text
A climate scientist uses a simulation to predict temperatures over 100 years. Which factor most directly affects the simulation's accuracy?
Answer: The quality and completeness of the real-world data used as inputs
Simulation accuracy depends on how well the input data and assumptions reflect real-world conditions.
In a traffic simulation, cars follow simplified rules rather than mimicking every driver behavior. This is an example of:
Answer: Abstraction used to make the simulation manageable
Simplifying complex behaviors into rules is abstraction, which makes simulations feasible to build and run.
A simulation produces different results each time it runs because it uses randomly generated inputs. This type of simulation is called:
Answer: Stochastic
A stochastic simulation incorporates randomness, producing different outputs on each run.
Why might a scientist run the same simulation hundreds of times with different random seeds?
Answer: To collect a range of outcomes and analyze the distribution of results
Running many trials with different random seeds gives a statistical distribution of outcomes rather than a single result.
A flight simulator accurately models aerodynamics but ignores weather turbulence. Which statement best describes this simulator?
Answer: It models some real-world aspects while abstracting away others
Simulations always involve trade-offs, modeling some aspects of reality while omitting or simplifying others.
Which of the following is a LIMITATION of using simulations instead of real-world experiments?
Answer: Simulation results depend on the accuracy of the underlying model and assumptions
If the model's assumptions are flawed or incomplete, simulation results may not reflect real-world behavior accurately.
A student simulates rolling two dice 10,000 times to estimate the probability of rolling a sum of 7. Why is a large number of trials important?
Answer: A larger sample size produces results closer to the true theoretical probability
By the law of large numbers, increasing the number of trials makes the experimental probability converge toward the theoretical probability.