Benfords Law Calculator
Analyze numerical datasets against Benford's Law leading digit distribution with expected vs observed percentages and Chi-square test statistic.
Understanding Benford's Law (First-Digit Law)
Benford's Law, also known as the First-Digit Law, is an empirical statistical law describing the frequency distribution of leading digits in naturally occurring numerical datasets. Contrary to intuition, the leading digits are not uniformly distributed (where each digit 1-9 would appear 11.1% of the time).
Benford's Law Logarithmic Formula
The probability $P(d)$ that a number begins with digit $d \in \{1, 2, \dots, 9\}$ is given by:
$$P(d) = \log_{10}\left(1 + \frac{1}{d}\right)$$
Expected leading digit percentages:
- Digit 1: 30.1%
- Digit 2: 17.6%
- Digit 3: 12.5%
- Digit 4: 9.7%
- Digit 5: 7.9%
- Digit 6: 6.7%
- Digit 7: 5.8%
- Digit 8: 5.1%
- Digit 9: 4.6%
Applications in Forensic Accounting and Fraud Detection
Because human-fabricated data tends to distribute digits uniformly or bias toward specific round numbers, auditors, tax authorities, and forensic accountants use Benford's Law analysis to detect anomalies in financial ledgers, tax returns, and scientific publications.
For further statistical analysis, explore our ANOVA Calculator and Z-Score Calculator.
Frequently Asked Questions
Why does digit 1 appear most frequently under Benford's Law?
Growth across orders of magnitude takes logarithmic time. To grow from 1 to 2 requires a 100% increase, while growing from 9 to 10 requires only an 11.1% increase, meaning values spend more time with a leading digit of 1.
Which datasets naturally follow Benford's Law?
Datasets that span several orders of magnitude (e.g. population sizes, stock prices, stream flow rates, transaction amounts) follow Benford's Law. Assigned numbers with upper/lower bounds (like human height or test scores) usually do not.
How is the Chi-Square test calculated for Benford's Law?
The Chi-Square test compares the observed count of each digit against the expected count computed from Benford's theoretical percentages to evaluate goodness of fit.