Herdan’s Law is a statistical principle that states that the variability of a measurement is inversely proportional to its precision.
In other words, as the precision of a statistic increases, the variability of that statistic decreases.
This principle is often used in research to reduce the number of measurements required in order to obtain a valid estimate.
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