A phenomenological law also called the first digit law, first digit phenomenon, or leading digit phenomenon. Benford's law states that in listings, tables of statistics,
etc., the digit 1 tends to occur with
probability , much greater
than the expected 11.1% (i.e., one digit out of 9). Benford's law can be observed,
for instance, by examining tables of logarithms
and noting that the first pages are much more worn and smudged than later pages (Newcomb
1881). While Benford's law unquestionably applies to many situations in the real
world, a satisfactory explanation has been given only recently through the work of
Hill (1998).
Benford's law was used by the character Charlie Eppes as an analogy to help solve a series of high burglaries in the Season 2 "The Running Man" episode (2006) of the television crime
drama NUMB3RS.
Benford's law applies to data that are not dimensionless, so the numerical values of the data depend on the units. If there exists a universal probability distribution
over such numbers, then it must be invariant
under a change of scale, so
 |
(1)
|
If , then ,
and normalization implies . Differentiating with respect
to and setting gives
 |
(2)
|
having solution . Although this is not a proper
probability distribution (since it diverges), both the laws of physics and human
convention impose cutoffs. For example, randomly selected street addresses obey something
close to Benford's law.
If many powers of 10 lie between the cutoffs, then the probability that the first (decimal) digit is is given by a logarithmic distribution
 |
(3)
|
for , ..., 9, illustrated above and tabulated below.
 |  |  |  | | 1 | 0.30103 | 6 | 0.0669468 | | 2 | 0.176091 | 7 | 0.0579919 | | 3 | 0.124939 | 8 | 0.0511525 | | 4 | 0.09691 | 9 | 0.0457575 | | 5 | 0.0791812 | | |
However, Benford's law applies not only to scale-invariant data, but also to numbers chosen from a variety of different sources. Explaining this fact requires a more
rigorous investigation of central
limit-like theorems for the mantissas
of random variables under multiplication.
As the number of variables increases, the density function approaches that of the
above logarithmic distribution. Hill (1998) rigorously demonstrated that the "distribution
of distributions" given by random samples taken from a variety of different
distributions is, in fact, Benford's law (Matthews).
One striking example of Benford's law is given by the 54 million real constants in Plouffe's "Inverse Symbolic Calculator" database, 30% of which begin with
the digit 1. Taking data from several
disparate sources, the table below shows the distribution of first digits as compiled
by Benford (1938) in his original paper.
| | | | | | | | | | | | | Col. | Title | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | Samples | | A | Rivers, Area | 31.0 | 16.4 | 10.7 | 11.3 | 7.2 | 8.6 | 5.5 | 4.2 | 5.1 | 335 | | B | Population | 33.9 | 20.4 | 14.2 | 8.1 | 7.2 | 6.2 | 4.1 | 3.7 | 2.2 | 3259 | | C | Constants | 41.3 | 14.4 | 4.8 | 8.6 | 10.6 | 5.8 | 1.0 | 2.9 | 10.6 | 104 | | D | Newspapers | 30.0 | 18.0 | 12.0 | 10.0 | 8.0 | 6.0 | 6.0 | 5.0 | 5.0 | 100 | | E | Specific Heat | 24.0 | 18.4 | 16.2 | 14.6 | 10.6 | 4.1 | 3.2 | 4.8 | 4.1 | 1389 | | F | Pressure | 29.6 | 18.3 | 12.8 | 9.8 | 8.3 | 6.4 | 5.7 | 4.4 | 4.7 | 703 | | G | H.P. Lost | 30.0 | 18.4 | 11.9 | 10.8 | 8.1 | 7.0 | 5.1 | 5.1 | 3.6 | 690 | | H | Mol. Wgt. | 26.7 | 25.2 | 15.4 | 10.8 | 6.7 | 5.1 | 4.1 | 2.8 | 3.2 | 1800 | | I | Drainage | 27.1 | 23.9 | 13.8 | 12.6 | 8.2 | 5.0 | 5.0 | 2.5 | 1.9 | 159 | | J | Atomic Wgt. | 47.2 | 18.7 | 5.5 | 4.4 | 6.6 | 4.4 | 3.3 | 4.4 | 5.5 | 91 | | K | ,  | 25.7 | 20.3 | 9.7 | 6.8 | 6.6 | 6.8 | 7.2 | 8.0 | 8.9 | 5000 | | L | Design | 26.8 | 14.8 | 14.3 | 7.5 | 8.3 | 8.4 | 7.0 | 7.3 | 5.6 | 560 | | M | Reader's Digest | 33.4 | 18.5 | 12.4 | 7.5 | 7.1 | 6.5 | 5.5 | 4.9 | 4.2 | 308 | | N | Cost
Data | 32.4 | 18.8 | 10.1 | 10.1 | 9.8 | 5.5 | 4.7 | 5.5 | 3.1 | 741 | | O | X-Ray Volts | 27.9 | 17.5 | 14.4 | 9.0 | 8.1 | 7.4 | 5.1 | 5.8 | 4.8 | 707 | | P | Am.
League | 32.7 | 17.6 | 12.6 | 9.8 | 7.4 | 6.4 | 4.9 | 5.6 | 3.0 | 1458 | | Q | Blackbody | 31.0 | 17.3 | 14.1 | 8.7 | 6.6 | 7.0 | 5.2 | 4.7 | 5.4 | 1165 | | R | Addresses | 28.9 | 19.2 | 12.6 | 8.8 | 8.5 | 6.4 | 5.6 | 5.0 | 5.0 | 342 | | S | ,  | 25.3 | 16.0 | 12.0 | 10.0 | 8.5 | 8.8 | 6.8 | 7.1 | 5.5 | 900 | | T | Death Rate | 27.0 | 18.6 | 15.7 | 9.4 | 6.7 | 6.5 | 7.2 | 4.8 | 4.1 | 418 | | Average | 30.6 | 18.5 | 12.4 | 9.4 | 8.0 | 6.4 | 5.1 | 4.9 | 4.7 | 1011 | | Probable Error |  |  |  |  |  |  |  |  | | |
The following table gives the distribution of the first digit of the mantissa following Benford's Law using a number of different methods.
| method | Sloane | sequence | | Sainte-Lague | A055439 | 1, 2, 3, 1, 4, 5, 6, 1, 2, 7,
8, 9, ... | | d'Hondt | A055440 | 1, 2, 1, 3, 1, 4, 2, 5, 1, 6, 3, 1, ... | | largest remainder, Hare quotas | A055441 | 1, 2, 3, 4, 1, 5, 6, 7, 1, 2,
8, 1, ... | | largest remainder, Droop quotas | A055442 | 1, 2, 3, 1, 4, 5, 6, 1, 2, 7, 8, 1, ... |
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