What does Benford's Law state about the distribution of the first digit in random data?

Benford's Law asserts that in many naturally occurring datasets, the first digit is more likely to be smaller. Specifically, it reveals that numbers beginning with the digit 1 occur more frequently than those starting with 2, 3, and so on, up to 9. This means that according to Benford's Law, approximately 30% of the numbers in a data set will begin with the digit 1, while only about 11% will start with 9.

This phenomenon arises because of the logarithmic scale of the number system itself, which influences the way numbers are distributed in various fields like finance, social science, and demographics. The skewed distribution aligns with the principle of scale invariance, where datasets that span several orders of magnitude naturally reflect this tendency, making option B the most accurate representation of Benford's Law.

Other potential answers do not align with Benford's findings. For example, stating that all digits are equally probable contradicts the core principle of Benford's Law. Similarly, suggesting a normal distribution misrepresents how data can behave, as many genuinely random datasets do not conform to a bell-curve shaped distribution. Human-generated numbers being in accordance with Benford's Law, while sometimes true,