Analyze data distribution to detect anomalies, fraud, or data manipulation using Benford's Law. Perfect for auditors, data analysts, and researchers.
Benford's Law states that in many naturally occurring datasets, the leading digit is more likely to be small (1 appears ~30% of the time, 9 appears ~5% of the time).
Widely used in forensic accounting to detect anomalies in financial data, tax returns, and election results.
Helps verify the authenticity of datasets in scientific research, population statistics, and economic data.
Doesn't prove fraud - only indicates anomalies. Works best with large datasets spanning multiple orders of magnitude.
Probability of digit d as first digit: P(d) = log₁₀(1 + 1/d) where d ∈ {1, 2, ..., 9}
First observed by Simon Newcomb in 1881, later popularized by Frank Benford in 1938. Used by IRS and auditors worldwide.