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title: "Random number generator seeds"
canonical: "https://modelassist.epixanalytics.com/space/EA/26575296/Random%20number%20generator%20seeds"
format: markdown
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There are many algorithms that have been developed to generate a series of random numbers between zero and one with equal probability density for all possible values. The basis for these algorithms is of no particular interest here. The reader is referred to [Johnson et al. (1993)](https://epixanalytics.atlassian.net/wiki/spaces/EA/pages/26579303/), [Johnson et al. (1994](https://epixanalytics.atlassian.net/wiki/spaces/EA/pages/26579303/), and [Johnson et al. (1995)](https://epixanalytics.atlassian.net/wiki/spaces/EA/pages/26579303/) for thorough reviews and lists of further references. What is of interest is that these algorithms will start with a value between zero and one, and all subsequent random numbers that are generated will rely on this initial *seed value*. Figure 1 illustrates how the random values between 0 and 1 (which is equal to a Uniform (0,1) distribution) is used directly or otherwise to generate most of the commonly used distributions in risk analysis.

  


Figure 1  
 

> Macro (gliffy)

  


Most risk analysis packages now offer the option to select a seed value. We personally do this as a matter of course, setting the seed to one (because one can remember it!). Providing the model is not changed, and that includes the position of the distributions in a spreadsheet model and therefore the order in which they are sampled, the same simulation results can be exactly repeated. More importantly, one or more distributions can be changed within the model and by running a second simulation one can look at the effect these changes have on the model's outputs. It is then certain that any observed change in the result is due to changes in the model and not a result of the randomness of the sampling.

  


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