How to Lie with Statistics
Chapters 8-10: Daniel Huff
Chapter 8: Post-Hoc Rides Again
• If B follows A, then A has caused B
– Perhaps neither of these things has produced
the other, but both are a product of some third
factor
– Correlation can actually be of any of several
types and can be limited to a range
– Given a small sample, you are likely to find
some substantial correlation between any pair
of characters or events
Chapter 8: Post-Hoc rides Again
• A common kind is when the relationship is
real but it is not possible to be sure which of
the variables is the cause and which is the
effect
– Perhaps there is a real correlation, yet neither of
the variables has any effect at all on the others
– Watch out for a correlation conclusion beyond
the data which it has been demonstrated. (Ex.
More rain = better crops)
Chapter 8: Post-Hoc Rides Again
• Negative correlation is a statement that as
one variable increases the other tends to
decrease (or visa-versa)
• Positive correlation is a statement that as
one variable decreases the other tends to
increase (or visa-versa).
Chapter 9: How to Statisculate
• Misinforming people by the use of
statistical material might be called statistical
manipulation.
• False charts in magazines and newspapers
frequently sensationalize by exaggeration,
rarely minimize anything
Chapter 9: How to Statisculate
• One of the trickiest ways to misrepresent
statistical data is by means of a map (Ex. National
income grouping, using the statistical average of
mean instead of the smaller and more informative
median, and assumes that income is directly
proportionate to size.)
• Using decimals as a way to lend improper
precision to statistics
Chapter 9: How to Statisculate
• Any percentage figure based on a small
number of cases is likely to be misleading
• The “shifting base” -- percentages taken off
different totals to imply different amounts
• Percentages added together, or
mathematically used in other ways (Ex. “I
mix ‘em fifty-fifty: one horse, one rabbit.”)
Chapter 9: How to Statisculate
• Statistics is as much an art as it is a science
– A great many manipulations and even distortions are
possible within the bounds of propriety. Often the
statistician must choose among methods, a subjective
process, and find the one that he/she will use to
represent the facts.
– This suggests giving statistical material, the facts and
figures in newspapers and books, magazines and
advertising, a very sharp second look before accepting
any of them.
Chapter 10: How to Talk Back to
a Statistic
• 1st thing to look for is bias
• Conscious bias
– Direct misstatements
– Ambiguous statement
– Selection of favorable data
• Suppression of unfavorable
• Units of measurement may be shifted
• Improper measure (trickery covered by the use of
the word “average”)
Chapter 10: How to Talk Back to
a Statistic
• Who says so? How do they know?
– A biased sample, or that has been selected
improperly or has selected itself
– Reported correlation: is it big enough to mean
anything? Are there enough cases to add up to
any significance? Look for a measure of
reliability (sources for error)
Chapter 10: How to Talk Back to
a Statistic
• What is missing?
– Look out for “average”: variety unspecified, a matter
where mean and median might be expected to differ
substantially
– Percentages are given and raw figures are missing
– The factor that caused change to occur, implying that
some other more desired factor is responsible (Ex.
Looking at total deaths rather than death rate, don’t
forget there are more people now than there used to be)
Chapter 10: How to Talk Back to
a Statistic
• Did somebody change the subject?
– Watch out for a switch somewhere between the
raw figure and the conclusion
– Strange things crop out when figures are based
on what people say -- even about things that
seem to be objective facts
Chapter 10: How to Talk Back to
a Statistic
• Does it make sense?
– Often cuts a statistic down to size when the
whole idea is based on an unproved assumption
– Use common sense
– The trend-to-now may be a fact, but the future
trend represents no more than an educated
guess