Re: seti@home IS WORKING

From: Michael S. Lorrey (mike@lorrey.com)
Date: Sat Jul 17 1999 - 13:45:04 MDT


Rob Harris Cen-IT wrote:
> > Math is math, and is the same math everywhere in the universe.
> >
> You and everyone else on this planet have absolutely no evidence whatsoever
> for this immense assumption.

On the contrary, I highly suggest you read the following....cheers,
Mike.

From:
http://www.newscientist.com/ns/19990710/thepowerof.html

The power of one

Everyday numbers obey a law so unexpected it is hard to believe it's
true.
Armed with this knowledge, says Robert Matthews, it's easy to catch
those
who have been faking research results or cooking the books.

ALEX HAD NO IDEA what dark little secret he was about to uncover when he
asked his brother-in-law to help him out with his term project. As an
accountancy student at Saint Mary's University in Halifax, Nova Scotia,
Alex
[not the student's real name] needed some real-life commercial figures
to
work on, and his brother-in-law's hardware store seemed the obvious
place to
get them.

Trawling through the year's sales figures, Alex could find nothing
obviously
strange about them. Still, he did what he was supposed to do for his
project, and performed a bizarre little ritual requested by his
accountancy
professor, Mark Nigrini. He went through the sales figures and made a
note
of how many started with the digit 1. It came out at 93 per cent. He
handed
it in and thought no more about it.

Later, when Nigrini was marking the coursework, he took one look at that
figure and realized that an embarrassing situation was looming. His
suspicions hardened as he looked through the rest of Alex's analysis of
his
brother-in-law's accounts. None of the sales figures began with the
digits 2
through to 7, and there were just 4 beginning with the digit 8, and 21
with
9. After a few more checks, Nigrini was in no doubt: Alex's
brother-in-law
was a fraudster, systematically cooking the books to avoid the
attentions of
bank managers and tax inspectors.

It was a nice try. At first glance, the sales figures showed nothing
very
suspicious, with none of the sudden leaps or dives that often attract
the
attentions of the authorities. But that was just it: they were too
regular.
And this is why they fell foul of that ritual he had asked Alex to
perform.

Because what Nigrini knew--and Alex's brother-in-law clearly didn't--was
that the digits making up the shop's sales figures should have followed
a
mathematical rule discovered accidentally over 100 years ago. Known as
Benford's law, it is a rule obeyed by a stunning variety of phenomena,
from
stock market prices to census data to the heat capacities of chemicals.
Even
a ragbag of figures extracted from newspapers will obey the law's
demands
that around 30 per cent of the numbers will start with a 1, 18 per cent
with
a 2, right down to just 4.6 per cent starting with a 9.

It is a law so unexpected that at first many people simply refuse to
believe
it can be true. Indeed, only in the past few years has a really solid
mathematical explanation of its existence emerged. But after years of
being
regarded as a mathematical curiosity, Benford's law is now being eyed by
everyone from tax inspectors to computer designers--all of whom think it
could help them solve some tricky problems with astonishing ease. In two
weeks' time, the US Institute of Internal Auditors will begin holding
training courses on how to apply Benford's law in fraud investigations,
hailing it as the biggest advance in the field for years.

The story behind the law's discovery is every bit as weird as the law
itself. In 1881, the American astronomer Simon Newcomb penned a note to
the
American Journal of Mathematics about a strange quirk he'd noticed about
books of logarithms, then widely used by scientists performing
calculations.
The first pages of such books seemed to get grubby much faster than the
last
ones.

The obvious explanation was perplexing. For some reason, people did more
calculations involving numbers starting with 1 than 8 and 9. Newcomb
came up
with a little formula that matched the pattern of use pretty well:
nature
seems to have a penchant for arranging numbers so that the proportion
beginning with the digit D is equal to log10 of 1 + (1/D) (see "Here,
there
and everywhere" below).

With no very convincing argument for why the formula should work,
Newcomb's
paper failed to arouse any interest, and the Grubby Pages Effect was
forgotten for over half a century. But in 1938, a physicist with the
General
Electric Company in the US, Frank Benford, rediscovered the effect and
came
up with the same law as Newcomb. But Benford went much further. Using
more
than 20 000 numbers culled from everything from listings of the drainage
areas of rivers to numbers appearing in old magazine articles, Benford
showed that they all followed the same basic law: around 30 per cent
began
with the digit 1, 18 per cent with 2 and so on.

Like Newcomb, Benford did not have any really good explanation for the
existence of the law. Even so, the sheer wealth of evidence he provided
to
demonstrate its reality and ubiquity has led to his name being linked
with
the law ever since.

It was nearly a quarter of a century before anyone came up with a
plausible
answer to the central question: why on earth should the law apply to so
many
different sources of numbers? The first big step came in 1961 with some
neat
lateral thinking by Roger Pinkham, a mathematician then at Rutgers
University in New Brunswick, New Jersey. Just suppose, said Pinkham,
there
really is a universal law governing the digits of numbers that describe
natural phenomena such as the drainage areas of rivers and the
properties of
chemicals. Then any such law must work regardless of what units are
used.
Even the inhabitants of the Planet Zob, who measure area in grondekis,
must
find exactly the same distribution of digits in drainage areas as we do,
using hectares. But how is this possible, if there are 87.331 hectares
to
the grondeki?

The answer, said Pinkham, lies in ensuring that the distribution of
digits
is unaffected by changes of units. Suppose you know the drainage area in
hectares for a million different rivers. Translating each of these
values
into grondekis will change the individual numbers, certainly. But
overall,
the distribution of numbers would still have the same pattern as before.
This is a property known as "scale invariance".

Pinkham showed mathematically that Benford's law is indeed
scale-invariant.
Crucially, however, he also showed that Benford's law is the only way to
distribute digits that has this property. In other words, any "law" of
digit
frequency with pretensions of universality has no choice but to be
Benford's
law.

Pinkham's work gave a major boost to the credibility of the law, and
prompted others to start taking it seriously and thinking up possible
applications. But a key question remained: just what kinds of numbers
could
be expected to follow Benford's law? Two rules of thumb quickly emerged.
For
a start, the sample of numbers should be big enough to give the
predicted
proportions a chance to assert themselves. Second, the numbers should be
free of artificial limits, and allowed to take pretty much any value
they
please. It is clearly pointless expecting, say, the prices of 10
different
types of beer to conform to Benford's law. Not only is the sample too
small,
but--more importantly--the prices are forced to stay within a fixed,
narrow
range by market forces.

Random numbers

On the other hand, truly random numbers won't conform to Benford's law
either: the proportions of leading digits in such numbers are, by
definition, equal. Benford's Law applies to numbers occupying the
"middle
ground" between the rigidly constrained and the utterly unfettered.

Precisely what this means remained a mystery until just three years ago,
when mathematician Theodore Hill of Georgia Institute of Technology in
Atlanta uncovered what appears to be the true origin of Benford's law.
It
comes, he realized, from the various ways that different kinds of
measurements tend to spread themselves. Ultimately, everything we can
measure in the Universe is the outcome of some process or other: the
random
jolts of atoms, say, or the exigencies of genetics. Mathematicians have
long
known that the spread of values for each of these follows some basic
mathematical rule. The heights of bank managers, say, follow the
bell-shaped
Gaussian curve, daily temperatures rise and fall in a wave-like pattern,
while the strength and frequency of earthquakes are linked by a
logarithmic
law.

Now imagine grabbing random handfuls of data from a hotchpotch of such
distributions. Hill proved that as you grab ever more of such numbers,
the
digits of these numbers will conform ever closer to a single, very
specific
law. This law is a kind of ultimate distribution, the "Distribution of
Distributions". And he showed that its mathematical form is...Benford's
Law.

Hill's theorem, published in 1996, seems finally to explain the
astonishing
ubiquity of Benford's law. For while numbers describing some phenomena
are
under the control of a single distribution such as the bell curve, many
more--describing everything from census data to stock market prices--are
dictated by a random mix of all kinds of distributions. If Hill's
theorem is
correct, this means that the digits of these data should follow
Benford's
law. And, as Benford's own monumental study and many others have showed,
they really do.

Mark Nigrini, Alex's former project supervisor and now a professor of
accountancy at the Southern Methodist University, Dallas, sees Hill's
theorem as a crucial breakthrough: "It . . . helps explain why the
significant-digit phenomenon appears in so many contexts."

It has also helped Nigrini to convince others that Benford's law is much
more than just a bit of mathematical frivolity. Over the past few years,
Nigrini has become the driving force behind a far from frivolous use of
the
law: fraud detection.

In a ground-breaking doctoral thesis published in 1992, Nigrini showed
that
many key features of accounts, from sales figures to expenses claims,
follow
Benford's law--and that deviations from the law can be quickly detected
using standard statistical tests. Nigrini calls the fraud-busting
technique
"digital analysis", and its successes are starting to attract interest
in
the corporate world and beyond.

Some of the earliest cases--including the sharp practices of Alex's
store-keeping brother-in-law--emerged from student projects set up by
Nigrini. But soon he was using digital analysis to unmask much bigger
frauds. One recent case involved an American leisure and travel company
with
a nationwide chain of motels. Using digital analysis, the company's
audit
director discovered something odd about the claims being made by the
supervisor of the company's healthcare department. "The first two digits
of
the healthcare payments were checked for conformity to Benford's law,
and
this revealed a spike in numbers beginning with the digits '65'," says
Nigrini. "An audit showed 13 fraudulent checks for between $6500 and
$6599...related to fraudulent heart surgery claims processed by the
supervisor, with the check ending up in her hands."

Benford's law had caught the supervisor out, despite her best efforts to
make the claims look plausible. "She carefully chose to make claims for
employees at motels with a higher than normal number of older
employees,"
says Nigrini. "The analysis also uncovered other fraudulent claims worth
around $1 million in total."

Not surprisingly, big businesses and central governments are now also
starting to take Benford's law seriously. "Digital analysis is being
used by
listed companies, large private companies, professional firms and
government
agencies in the US and Europe--and by one of the world's biggest audit
firms," says Nigrini.

Warning signs

The technique is also attracting interest from those hunting for other
kinds
of fraud. At the International Institute for Drug Development in
Brussels,
Mark Buyse and his colleagues believe Benford's law could reveal
suspicious
data in clinical trials, while a number of university researchers have
contacted Nigrini to find out if digital analysis could help reveal
fraud in
laboratory notebooks.

Inevitably, the increasing use of digital analysis will lead to greater
awareness of its power by fraudsters. But according to Nigrini, that
knowledge won't do them much good--apart from warning them off: "The
problem
for fraudsters is that they have no idea what the whole picture looks
like
until all the data are in," says Nigrini. "Frauds usually involve just a
part of a data set, but the fraudsters don't know how that set will be
analyzed: by quarter, say, or department, or by region. Ensuring the
fraud
always complies with Benford's Law is going to be tough--and most
fraudsters
aren't rocket scientists."

In any case, says Nigrini, there is more to Benford's law than tracking
down
fraudsters. Take the data explosion that threatens to overwhelm computer
data storage technology. Mathematician Peter Schatte at the Bergakademie
Technical University, Freiberg, has come up with rules that optimize
computer data storage, by allocating disk space according to the
proportions
dictated by Benford's law.

Ted Hill at Georgia Tech thinks that the ubiquity of Benford's law could
also prove useful to those such as Treasury forecasters and demographers
who
need a simple "reality check" for their mathematical models. "Nigrini
showed
recently that the populations of the 3000-plus counties in the US are
very
close to Benford's law," says Hill. "That suggests it could be a test
for
models which predict future populations--if the figures predicted are
not
close to Benford, then rethink the model."

Both Nigrini and Hill stress that Benford's law is not a panacea for
fraud-busters or the world's data-crunching ills. Deviations from the
law's
predictions can be caused by nothing more nefarious than people rounding
numbers up or down, for example. And both accept that there is plenty of
scope for making a hash of applying it to real-life situations: "Every
mathematical theorem or statistical test can be misused--that does not
worry
me," says Hill.

But they share a sense that there are some really clever uses of
Benford's
law still waiting to be dreamt up. Says Hill: "For me the law is a prime
example of a mathematical idea which is a surprise to everyone--even the
experts."

Robert Matthews is Science Correspondent for The Sunday Telegraph

Here, there and everywhere

NATURE'S PREFERENCES for certain numbers and sequences has long
fascinated
mathematicians. The so-called Golden Mean-- roughly equal to 1.62 and
supposedly giving the most aesthetically pleasing dimensions for
rectangles--has been found lurking in all kinds of places, from
seashells to
knots, while the Fibonacci sequence--1, 1, 2, 3, 5, 8 and so on, every
figure being the sum of its two predecessors--crops up everywhere in
nature,
from the arrangement of leaves on plants to the pattern on pineapple
skins.
Benford's law appears to be another fundamental feature of the
mathematical
universe, with the proportion of numbers starting with the digit D given
by
log10 of 1 + (1/D). In other words, around 100 x log2 (30 per cent) of
such
numbers will begin with "1"; 100 x log1.5 (17.6 per cent) with "2"; down
to
100 x log1.11 (4.6 per cent) with "9". But the mathematics of Benford's
law
goes further, predicting the proportion of digits in the rest of the
numbers
as well. For example, the law predicts that "0" is the most likely
second
digit--accounting for around 12 per cent of all second digits--while 9
is
the least likely, at 8.5 per cent. Benford's law thus suggests that the
most
common non-random numbers are those starting with "10...", which should
be
almost 10 times more abundant than the least likely, which will be those
starting "99...". As one might expect, Benford's law predicts that the
relative proportions of 1, 2, 3 and so on making up later digits of
numbers
become progressively more even, tending towards precisely 10 per cent
for
the least significant digit of every large number. In a nice little
twist,
it turns out that the Fibonacci sequence, the Golden Mean and Benford's
law
are all linked. The ratio of successive terms in a Fibonacci sequence
tend
toward the golden mean, while the digits of all the numbers making up
the
Fibonacci sequence tend to conform to Benford's law.

Further reading:
Digital Analysis Tests and Statistics, written and published by Mark
Nigrini, is available from mark_nigrini@msn.com
Eric Weisstein's Treasure Troves of Science - Benford's Law page



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