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Learning to model the problem

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The real art in developing Monte Carlo models lies in translating a real-world problem into Excel equations.  This is a skill you can develop over time.  The examples later in this tutorial will give you a good start.

As a first example, look at the case of a single coin toss.  In the real world we think in terms of "heads" and "tails", but for data analysis it makes much more sense to translate these outcomes to 0 and 1.  Next you have to figure out how to convert the output generated by the RAND() function into the output of a coin toss -- i.e., take evenly distributed randomly generated numbers greater than or equal to 0 and less than 1, and translate them into two single outcomes - 0 or 1 - with a 50% probability of each.

Of course the shortcut is to use the RANDBETWEEN() function.  The following formula entered into a worksheet cell would give exactly the desired output:  "=RANDBETWEEN(0, 1)".

As your model variables increase in complexity, however, it's important to master the art of RAND() manipulation.  For the coin toss, a simple approach would be "=ROUND(RAND(),0)".  Another approach that works equally well is "=INT(RAND()*2)".

Problems with more complex input patterns require a little more creativity.  For example, suppose your problem contains a weather variable, and you know from research that in your area on a given day there is a 20% chance of rain, a 5% chance of snow, and a 75% chance of zero precipitation.

For the output, let's assume 0 = no precipitation, 1 = rain, and 2 = snow.

One approach is simply to use nested IF() statements, as illustrated in the example below.  Cell A1 contains "=RAND()".  Cell A3 contains the nested IF() equation "=IF(A1<0.05,2,IF(A1<0.25,1,0))".

Another approach to the same problem would be to use a lookup table.  Often several approaches can solve the same problem.  When one approach becomes overly complex, try using your creative capacity to find a more elegant solution.

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