An estimation error is the difference between an estimator and the statistical parameter it estimates. It is a random variable before observing the sample. Its mean is the bias of the estimator, and its mean square is the sum of the variance and squared bias. Standardizing an estimation error by its standard error often yields an approximate standard normal distribution, allowing construction of a Wald confidence interval.
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