Random Numbers allow a simulation to behave in a random way, within the limits you set. This means they can exhibit real life forms of behavior, based around a Probability Distribution Random Numbers can be best described by example. Take, for example a simple dice. There is a 1 in 6 chance of each side of the dice coming up following a throw - some people would call this an equal probability of being sampled. Anyone who has played a board game knows that it doesn't seem like an equal chance of any side coming up, but of you throw a dice often enough you'll see that in the long term there is a 1 out of 6 chance of any side coming up. SIMUL8 random numbers are organized into 30,000 individual sets. This means that you have a "virtually" unlimited set to draw from. Each Object in a simulation can use a different Distribution (like Normal or Exponential) meaning that you can get as close as possible to real life conditions. The default in SIMUL8 is to use the same set of random numbers over and over again, with new streams available by clicking the Dice button

Numbers generated in an unpredictable, haphazard sequence.

Numbers that allow a researcher to choose participants purely by chance; usually generated by a computer.

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