Statistically speaking, you may be wrong

Statistics are mighty nuggets of proof that can further any argument or cause. They tell nay-sayers where to shove it. And journalists love them for two reasons: statistics make headlines, and they simplify the message for media consumers.

The problem lies in those who—whether intentionally or not—incorrectly interpret and communicate statistics to those they wish to influence.

As an example, your organization’s mission
is to help save the whales. You come across
a fantastic statistic that supports your cause:
saving the whales is a top-five environmental
concern among Canadians. Perfect! The statistic
becomes part of your key messages, and you
always make sure to share it during media
interviews. Journalists eat it up, and pretty soon
your organization is experiencing a surge in
financial donations.

You may be able to argue that the statistic is
technically accurate. But what you have chosen
not to mention in your interviews is the following:

- “saving the whales” was number five of seven
   options provided to those polled;

- “among Canadians” actually refers to a small
   number of random people who were not
   representative of the entire makeup of the
   country (e.g., in terms of ethnicity, financial
   status etc.); and

- the statistic came from a source with whom

   you are not familiar.

As you can see, when it comes to credibility,

context can giveth or taketh away.

Sadly, part of the problem lies with the general

public. Too often, we rely on statistics as fact
without knowing or even stopping to consider the
context. Perhaps this is a symptom of living in a
fast-paced world of information overload—we
simply have no time to question validity, and instead
scan the news for “nuggets” that we can store in
our minds and share with friends over drinks.

However, I ultimately believe that organizations
need to take responsibility for the messages they
distribute. It is simply unethical to intentionally
mislead audiences—and even if organizations are
unaware they are doing so, they should always question
the validity of any statistic before they disperse it to
the masses.

Handout: Using Statistics
Statistics Can Be Misleading
Health Statistics Can Be Manipulated