Causal Inference
Sampling error refers to the difference between the characteristics of a sample and the characteristics of the entire population from which it is drawn. This error arises because a sample does not perfectly represent the population, leading to potential inaccuracies in estimates derived from that sample. Understanding sampling error is crucial in sampling and estimation as it highlights the limitations and uncertainties involved in making inferences about a population based on a subset.
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