Sampling error is the deviation between the estimate of an ideal sample and the true population. To get around these constraints, black belts or statisticians extract the samples from the statistical population and make inferences about the population. We would be unlikely to use sampling when the events and products are unique and cannot be replicable. In a DMAIC sense, this is most common in the Measure phase. Instead, they use exit polls to derive statistical conclusions about the population as a whole.
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