Implementing Random Sampling Shawn Burke – Simple Random a true random sample is more complex that most people think, but there are a number of viable ways to build a random sample from different types of populations.  In general, the first and most important step is to organize the identities of your population into a set that can be numbered, since numbers are relatively easy to randomize.Once each member of your population is assigned to a unique numeric identifier, there are a few ways to choose your actual sample:

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Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions.