Asymptotic normality refers to the property of a sequence of estimators that, as the sample size increases, their distribution approaches a normal distribution. This concept is crucial in statistical inference, particularly in understanding how estimators behave as the amount of data grows, allowing for the application of normal-based techniques for estimation and hypothesis testing.
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