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Part V: Statistical Studies and the Hunt for a Meaningful Relationship
of all teens. This discrepancy means that although fewer teens in the sample
used Ecstasy that year, the difference wasn’t enough to account for more
than chance variability from sample to sample. (See Chapter 14 for more
about statistical significance.)
Headlines and leading paragraphs in press releases and news articles often
overstate the actual results of a study. Big results, spectacular findings, and
major breakthroughs make the news these days, and reporters and others in
the media constantly push the envelope in terms of what is and isn’t newswor-
thy. How can you sort out the truth from exaggeration? The best thing to do is
to read the fine print.
Taking the results one step beyond the actual data
A study that links having children later in life to longer life spans illustrates
another point about research results. Do the results of this observational
study mean that having a baby later in life can make you live longer? “No,”
said the researchers. Their explanation of the results was that having a baby
later in life may be due to women having a “slower” biological clock, which
presumably would then result in the aging process being slowed down.
My question to these researchers is, “Then why didn’t you study that, instead
of just looking at their ages?” The study didn’t include any information that
would lead me to conclude that women who had children after age 40 aged
at a slower rate than other women, so in my view, the researchers shouldn’t
make that conclusion. Or the researchers should state clearly that this view
is only a theory and requires further study. Based on the data in this study,
the researchers’ theory seems like a leap of faith (although since I became a
new mom at age 41, I’ll hope for the best!).
Frequently in a press release or news article, the researcher will give an
explanation about why he thinks the results of the study turned out the way
they did and what implications these results have for society as a whole
when the “why” hasn’t been studied yet. These explanations may have been
in response to a reporter’s questions about the research — questions that
were later edited out of the story, leaving only the juicy quotes from the
researcher. Many of these after-the-fact explanations are no more than theo-
ries that have yet to be tested. In such cases, you should be wary of conclu-
sions, explanations, or links drawn by researchers that aren’t backed up by
their studies.
Be aware that the media wants to make you read the article (they get paid
to do that), so they will have strong headlines, or will make unconfirmed
“cause-effect” statements because it is their job to sell the story. It is your job
to be wary.

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