I am new to simulation and would like to do what I hope is a simple case.
I have a dataset with an N of 85. The data consists of the weights of truckloads of material that were weighed with scales, and data that estimates the weight based on machine performance. The estimate by truckload is interesting and can be off for an individual load by a good margin enough, but what most end users will care about is its accuracy over the course of an entire field... 80 truckloads. So it's the sum of the predictions that matters to me. So I want to run a simulation where I randomly draw 5%, 10%, 15%, 20% etc of the loads, run a regression on those, apply it to the entire population, and see where the variability in the error between cummulative predicted mass, and the cummulative weighed mass becomes acceptable from a practical standpoint. Is this something I can execute with do loops? Or would it be possible to do it with proc surveyselect and a do loop? Perhaps there are some good online examples or primers out there?
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