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Benford's law calculator

Explore the unequal leading-digit frequencies predicted by Benford's law. Use the data comparison only when a Benford model is plausible for the measurements.

Calculator

Expected digit probability
30.103000%
Expected count for selected digit
301.029996
Non-zero observations
1,000.000000
Zeros ignored
0.000000
Leading-digit comparison
DigitBenford probabilityExpected countObserved count
1.0000000.301030301.029996Not supplied
2.0000000.176091176.091259Not supplied
3.0000000.124939124.938737Not supplied
4.0000000.09691096.910013Not supplied
5.0000000.07918179.181246Not supplied
6.0000000.06694766.946790Not supplied
7.0000000.05799257.991947Not supplied
8.0000000.05115351.152522Not supplied
9.0000000.04575745.757491Not supplied

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How this calculator works

First-digit probabilities decline from digit 1 to digit 9. Data mode takes the first significant decimal digit of each absolute non-zero value, ignoring zeros and signs. The comparison statistic measures discrepancy but supplies no fraud verdict. Assigned identifiers, constrained ranges and minimum purchase prices often make Benford assumptions inappropriate.

Formula

P(D=d) = log10(1+1/d), d = 1,...,9; expected_d = N P(D=d); χ² = Σ(observed_d-expected_d)²/expected_d.

Worked example

Digit 1 has probability log10(2) = 0.301030. In 1,000 suitable observations its expected count is about 301.03, rather than 111.11.

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Frequently asked questions

Does every data set follow this law?

No. Benford behaviour usually needs suitable scale variation and a generating process that does not assign the digits.

How are decimals and negatives handled?

Signs are ignored and the first non-zero significant digit is used. For example, -0.0042 contributes digit 4.

Does disagreement prove manipulation?

No. It may reflect an unsuitable model, rounding, sampling or ordinary variation.

Sources

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