Week 3 540 Mat

WK 3 DIS 1

WHY DO WE USE PSEUDORANDOM NUMBERS IN SIMULATIONS?

Generation of random numbers is not a simple process. In order for a number to be truly random it must be uniformly distributed (each random number in the interval of random numbers has equal chance of being selected), efficiently generated (the random numbers should not degenerate into constant values or recycle too frequently) and absent of patterns. Computers can generate random numbers using a mathematical process that artificially creates psuedorandom numbers more efficiently than true random numbers can be generated in a process akin to spinning the roulette wheel.

How do pseudorandom numbers affect the accuracy of a simulation?

Pseudo random numbers are often used in simulations and experiments because it’s impossible to model a truly random process. If there is a pattern to the numbers used, then there may be some borderline cases which are missed by the system. If one is not careful, pseudorandom numbers may threaten the accuracy of the simulation.

Week 3 Dis 2

What is the role of statistical analysis in simulation?

Statistical analysis is essential to identifying the critical factors in simulation. Performing the analysis of variance is to ensure the proper selection of significant factors. With this, understanding and judgment become more effective in making appropriate decisions regarding the product and process designs.

The purpose of statistical analysis is to determine the normal (probable) behavior of a simulation and distinguish it from abnormal (improbable) behavior of a system. In other words, we want to distinguish what happens commonly from what merely happens by chance.

For example, if our simulation models traffic and a truck flips over on the freeway, a statistical analysis would determine whether such an accident happens often or if this was simply an unlucky day for the driver and the accident happened by chance.

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