Modeling Discrete & Stochastic Events

It’s generally a good idea to begin thinking about your models with continuous time and quantities, particularly for strategic applications where you care about the big picture. But there are times when it matters that quantities are discrete – you can’t ride half a horse. Here’s a quick look at modeling such situations, starting with a pulse of arriving people:

The model is: discrete 1.mdl

Here’s a followup, incorporating random processes:

The model: stochastic 1.mdl

And finally, a more practical example that puts it all together:

The model: lemonade 1.mdl






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