CASE ASSIGNMENT
The case focuses on the power of statistics to influence and convince, but also to distort and
deceive. Consumer responsibility in interpreting reported findings is emphasized.
LYING STATISTICS
Three kinds of lies are possible, according to Benjamin Disraeli, a British prime minister in the
nineteenth century—lies, damned lies, and statistics. A related notion exists that “you can prove
anything with statistics.” Such statements bolster the distrust that many people have for statistical
analysis. On the other hand, many non-mathematicians hold quantitative data in awe, believing
that numbers are, or at least should be, unquestionably correct. Consequently, it comes as a shock
that various research studies can produce very different, often contradictory results. To solve this
paradox, many naive observers conclude that statistics must not really provide reliable indicators
of reality after all, and if statistics aren’t “right,” they must be “wrong.” It is easy to see how even
intelligent, well-educated people can become cynical if they don’t understand the concepts of
statistical reasoning and analysis.
Consider, for instance, the frequent reporting of a “scientific discovery” in the fields of
health and nutrition. The United States has become a nation of nervous people, ready to give up
eating pleasures at the drop of a medical report. Today’s “bad-for-you” food was probably once
good for you, and vice versa. Twenty years ago, many consumers were turned away from
consuming real butter to oily margarine, only recently to learn that the synthetically solidified oils
of margarine, trans-fatty acids, are worse for our arteries than any fat found in nature. In the year
following the publication of this finding, margarine sales dropped 8.2 percent and butter sales
rose 1.4 percent.
Distrust also arises concerning studies that link exercise to health. Numerous studies have
established statistically that people who exercise live longer. But the conclusion that exercise is
good for you may put the cart before the horse. Are people healthy because they exercise? Or do
they exercise because they are healthy? Correlation, once again, does not establish causation.
How do such incorrect and partial research findings become published and consequently
disseminated through the media? Some of the responsibility should probably be cast upon
researchers who may overstate the significance or the generalizability of their findings. The
media should also shoulder some blame, as preliminary findings of small or limited studies are
often reported as foregone conclusions. Consumers should also assume some responsibility in the
interpretation of reported research. Questions such as the following should be asked when
considering the value of reported findings.
Is the study sample representative of the population involved?
Were the statistical procedures used appropriate to the data?
Has the research involved a sample of significant size and a sufficient time period of study?
Were adequate controls applied to assure that outcomes are actually the result of the studied
variable?
Has the margin for error been taken into account in interpreting the results?
© 2015 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a
publicly accessible website, in whole or in part.
7