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**Random BuiltIn Function in Stella**

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**RANDOM(<min>, <max>, [<seed>])**

The RANDOM builtin generates a series of uniformly distributed random numbers between min and max. RANDOM samples a new random number in each iteration of a model run. If you wish to replicate the stream of random numbers, specify seed as an integer between 1 and To replicate a simulation, all entities that use statistical functions must have seeds specified. Each entity using a statistical function should use a separate seed value.

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Examples: RANDOM(0,1) creates a non-replicable uniformly distributed stream of numbers between 0 and 1. RANDOM(0,1,147) creates a replicable uniformly distributed stream of numbers between 0 and 1. RANDOM(0,10,12) gives a replicable uniformly distributed stream of numbers between 0 and 10. RANDOM(10,13,12) gives a replicable uniformly distributed stream of numbers between 10 and 13.

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**Build the flower model of Chapter 6 to reproduce **

the output shown on the next page. Or get it from

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**Now add a new converter for temperature and connect it**

To the intrinsic growth rate. In the original model the intrinsic growth rate was fixed at Here we’ll let Temperature be Random (20,30,999) and intrinsic growth rate = temperature/25.0 We added the seed here so all simulations will look the same.

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**Paste your resulting graphs of**

Flower area, growth, and decay here.

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**Try letting Temperature be Random (15,35,999)**

and intrinsic growth rate = temperature/25.0 What do you expect to be different for this new simulation? ANSWER

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**Paste your resulting graphs of**

Flower area, growth, and decay here.

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**NORMAL(<mean>,<std>, [<seed>])**

The NORMAL builtin generates a series of normally distributed random numbers with a specified mean and std (standard deviation). NORMAL samples a new random number in each iteration of a simulation. If you wish to replicate the stream of random numbers, specify seed as an integer between 1 and To replicate a simulation, all entities that use statistical functions must have seeds specified. Each entity using a statistical function should use a separate seed value.

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Examples: NORMAL(0,1) gives a non-replicable normally distributed stream of numbers (mean=0, standard deviation=1) NORMAL(0,1,147) gives a replicable normally distributed stream of numbers (mean=0, standard deviation=1) NORMAL(5,1,12) gives a replicable normally distributed stream of numbers (mean=5, standard deviation=1) NORMAL(10,5,102) gives a replicable normally distributed stream of numbers (mean=10, standard deviation=5)

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**Now let Temperature be Normal (25,5,999)**

and intrinsic growth rate = temperature/25.0 We added the seed here so all simulations will look the same and make it easier for your instructor to see if you got things set correctly.

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**Paste your resulting graphs of**

Flower area, growth, and decay here.

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**Now let Temperature be Normal (25,10,999)**

and intrinsic growth rate = temperature/25.0 What do you expect to be different for this new simulation? ANSWER

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**Paste your resulting graphs of**

Flower area, growth, and decay here.

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**Download the 3rd version of the MonoLake Model.**

This has a comparitive graph set for volume in the lake.

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**Run the model once to get a graph of water in the lake with a fixed export of 100.**

Now run with export set to Normal (100,50,999) . Run this 7 times.(don’t expect big things here) Now run with export set to Normal (100,50) . Run this 7 times

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**Paste your resulting graphs of**

Flower area, growth, and decay here.

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**Comment on the advantages and disadvantage of the seed**

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