Using JMP to Select a Simple Random Sample

The concept of a random sample is straightforward: choose a subset of a population, taking steps to ensure that all equally sized subsets share the same chance of selection. In practice, there are two common obstacles to random sampling: We often don't know the precise size or the identities of all members of the population. While common, these obstacles are easily overcome, but the resulting samples are not simple random samples, strictly speaking. In this section, we'll confine our attention to two ways in which we can use JMP to select a simple random sample.

To choose n observations as a simple random sample, we need a way to gather or list all elements in the population. This is known as a sampling ...

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