Statistical Lies and The Liars Who Use Them
August 16, 2013
In his book, Stat-Spotting, Joel Best gives a good
example of how politicians can lie with statistics. He explains
how President Bush's Secretary of the Interior Gale Norton went
before reporters and announced that the United States had had
its first net gain in wetlands since the Fish and Wildlife Service
started tracking wetland acreage in 1954. That certainly makes
it sound like the administration and its agencies are doing a
good job protecting the environment, doesn't it? But it turns
out that the only reason there was a supposed increase in wetlands
acreage is because the term was defined in a new way, and now
included water hazards on golf courses and other man-made water
areas. She did not mention that the report she was referring
to in the "good news" acknowledged that the acreage
of natural wetland areas had declined once again.
Nice trick. We could redefine "lake" in such a way
that thousands of ponds are classified as lakes, and then claim
to have "created" thousands of new natural lakes. The
bottom line is that when comparing current data with that from
the past, you have to be comparing the same thing to be accurate
and honest. It might make sense to include man-made wetlands
in the definition, but then the older data should be adjusted
(if possible) to include these as well, if there are comparisons
to be made.
Best gives another good example of questionable use of statistics
in his book. There was a report done by the Cable News Network
(CNN) in 2005, in which they looked at American wealth. They
reported that "the average U.S. household has a net worth
of greater than $400,000." But there is more than one way
to arrive at an average. In this case they decided to use the
mean rather than the median. In other words they added up the
net worth of all households and divided by the number of households.
Why this can distort the truth of the matter is clear if we imagine
a simple example.
Suppose there are a thousand people living on an island, which
we'll call Statland. One of them has a billion dollars and the
others all have nothing. The total of all assets is a billion
dollars, so if we divide that by the thousand residents we arrive
at a mean average net worth of one million dollars. Now, if we
report that "the average resident of Statland is worth a
million dollars," that might be accurate in one sense, but
it does give an inaccurate impression of a place where 99.9%
of the population is poor.
The median is arrived at by finding the measure where half
fall below and half above. At the time when CNN reported the
average net worth of U.S. households to be over $400,000, the
median net worth of households (including home equity) was about
$86,000. In other words, half of all households fell below this
figure and half above. While not as extreme a difference as in
Statland, the two figures do provide quite a differing view of
the wealth of families in The United States, don't they?
For more on the misuse of statistics, see our page on lying
with statistics. I detail several methods there which are
used to distort the truth for political purposes. For example,
I briefly address the way polls are manipulated through the wording
of the questions on them. You can easily get very different results
if you change how you ask a question.
I also have a page on my brainpower website that looks at
to lie with statistics. It covers issues like non-random
sampling and biased selection of data. I also look at how the
phrase "up to" is used to distort what the statistics
We should not be too surprised by the many statistical lies
we see. Any tool can be used for various purposes, both good
and bad, honest and dishonest. This is certainly true of the
powerful tool that we call statistics.
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