The Verbal Cheap Shot Artist Part 12: The Appeal to Statistics

This is part 12 of a 12 week series where I explore the tactics of verbal cheap shot artists – people who can’t, or won’t use valid arguments to present their case, but instead resort to verbal cheap shots. To make sure you don’t miss a single article, be sure and sign up for my RSS feed or subscribe by email (both are free!) so you can get the freshest new articles! Check out my other posts in the Verbal Cheap Shots category.

The true number of verbal fallacies is much larger than 12 but I’ve focused on some of the more common ones over the last 12 weeks, and this last one, the appeal to statistics, is potentially one of the most devious.

“Figures never lie, but liars figure.” –long forgotten statistics professor at The University of Alabama

While watching a television program recently, the narrator mentioned that six people die in a motor vehicle crash in the US every minute. The average person just accepts those type of statistics and believes that “something must be done!” But just doing a little math, yields that 3,150,600 people die each year in motor vehicle accidents … except that statistic isn’t true. The real number is closer to 42,000. Not anything to discount because each death is a tragedy, but a far smaller number than originally claimed.

With a shrug and a “wow,” people tend to accept most statistics as facts, after all, they sound SO scientific! But statistics are created by people, and many, if not most, of those people have agendas. When statistics about social problems (such as health care or teen pregnancy) are quoted as fact, many times the statistics come from activists who embellish the problem in order to increase funding or drum up concern. When not produced by activists, statistics are often created by a governmental agency, which may be motivated to play down or play up a problem … depending on which direction gives the politician the most power or television “face time”. Lastly, those statistics may be produced by corporations that have their own agenda, whether to increase sales or influence legislation.

How to dissect statistics

1. Who created it?
2. Why was it created?
3. How was it created?

If the source has a motive for exaggerating or downplaying the statistic or if it was created to advance a particular cause, influence legislation, or to sell a product, the answers to questions 1 and 2 may give plenty of reasons to doubt the statistic’s accuracy. If you can answer the first two questions, you may be able to see through any bias embedded in the statistic. That just leaves question 3.

How flawed statistics are produced

1. Poor samples
• The sample size is too small. Four out of five third graders haven’t taken a shower today really only means something if you check with more than five kids.
• The sample isn’t representative of the population. Political pollsters regularly use this one by “poisoning the well” and using a sample that already meets their ideology.
2. Inaccurate measurements. Improperly worded questions, vague definitions, decisions to include borderline cases, generalizations, and misinterpretations can all lead to inaccurate measurements and flawed statistics.
3. Guessing. Believe it or not, many governmental statistics are outright guesses. Statistics on unemployment, unreported crime, or other unreported issues are next to impossible to accurately predict, yet policy is made on their basis. Doesn’t make sense, does it?

Statistics sound credible, authoritative, and scientific, but in the wrong hands, they can lead to wrong conclusions. They can help point out where advertising needs to focus, where management needs to staff more people, and where employee theft is an overwhelming problem, but they can also waste resources and get the wrong people fired.

The next time you’re presented with a statistic, take a moment and examine it. Does it make sense? How and why was it created? Who created it?

The accurate answers to these questions may lead you in an entirely different direction.

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