In the context of statistical theory, particularly in the study of statistical inference and hypothesis testing, a "normal invariant" refers to certain properties or distributions that remain unchanged (invariant) under transformations or manipulations involving normal distributions. More formally, a statistic or an estimator is said to be invariant if its distribution does not change when the data undergoes certain transformations, such as changes in scale or location.
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