1. _______provides a laboratory for experimentation so that the _____ is not dis
ID: 3230445 • Letter: 1
Question
1. _______provides a laboratory for experimentation so that the _____ is not disrupted.
Linear Programming, Real System
Simulation Modeling, Cybernetic System
Linear Programming, Cybernetic System
Simulation Modeling, Real System
2. Complex simulation models most often are developed and run using?
QM for Windows
Excel Spreadsheets
Manual Analytical computations
simulation software (various brands)
3. In assigning random numbers in a Monte Carlo simulation?
it is important to use a normal distribution for all variables simulated.
All of these
it is not important to assign probabilities to an exact range of random number intervals.
none of these
it is important to develop a cumulative probability distribution.
4. is not part of a Monte Carlo simulation?
finding an optimal soulution
analyzing a real problem
evaluating the results
analyzing the results
Explanation / Answer
1. _______provides a laboratory for experimentation so that the _____ is not disrupted.
Linear Programming, Real System
Simulation Modeling, Cybernetic System
Linear Programming, Cybernetic System
Simulation Modeling, Real System ## this is the correct answer , we simulate the uncertainity to arrive at the results without touching the real systems. However , the uncertainty has its own chances of errors
2. Complex simulation models most often are developed and run using?
QM for Windows
Excel Spreadsheets
Manual Analytical computations
simulation software (various brands) ## while simple monte carlo simulations can be done in excel, advanced and complex simulations would require the simulations softwares that takes into account distributions , scenarios and constraints .
3. In assigning random numbers in a Monte Carlo simulation?
it is important to use a normal distribution for all variables simulated.
All of these
it is not important to assign probabilities to an exact range of random number intervals.
none of these ## simualtions are carried out based on the available information. There are no constraints on simulating the variables , except that they must allign to the business objective we are trying to solve.
it is important to develop a cumulative probability distribution.
4. is not part of a Monte Carlo simulation?
finding an optimal soulution ### we simulate situations to find a close answer. We do not do optimations in monte carlo simulations as the exact values or observations are not known
analyzing a real problem
evaluating the results
analyzing the results
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