It is more difficult to identify significant deviations from Benford's profile in small data sets.

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As the sample size gets smaller, the statistical power decreases, making it harder to identify significant deviations from Benford's profile. This is because small data sets are more prone to random fluctuations and outliers, which can obscure any underlying patterns or trends. In contrast, larger data sets tend to be more representative of the population and are better suited for detecting deviations from theoretical distributions like Benford's law.

It Is More Difficult to Identify Significant Deviations from Benford's