What is the purpose of defining the number of trials before running Monte Carlo simulations?

• A. To maximize computational time.
• B. To ensure there is a guaranteed win.
• C. To minimize perceived randomness.
• D. To balance computational effort against statistical precision.

Answer: (D)

Defining how many trials to run sets the amount of sampling used to estimate quantities from a Monte Carlo study. Each trial draws random inputs and records an outcome, so more trials provide more information about the distribution of results. As the number of trials grows, the estimate of an expected value (and related statistics) becomes more precise, and confidence intervals around that estimate tighten. This happens because of the Law of Large Numbers and the way sampling error decreases roughly with the square root of the number of trials. But more trials require more computation, so you choose a number that balances the computational effort with the desired level of precision. It’s not about maximizing time, guaranteeing a win, or eliminating randomness—randomness is inherent. The aim is to achieve an accurate estimate efficiently.