Averages are the "one-size-fits-all" of the risk management world, the "beige paint" of statistics. They're the person at a party who only talks about the weather, never offending anyone but never delighting anyone either. So what's the beef with averages? Well, let's dig in.
Firstly, let's talk about Bill Gates walking into a bar. No, it's not the setup to a bad joke; it's a statistical nightmare. The moment he strolls in, everyone in that establishment's "average" net worth skyrockets. Congratulations, you're now a millionaire—on paper. But try explaining that to your bank when you want a loan for a private jet.
Averages don't account for outliers, those pesky extremities that make life interesting, and statistics misleading. Consider, for example, that the average height for adult men in the U.S. is around 175 cm (5'9"). But if you're making a door frame based on that average, watch out for the NBA players coming to your "average-sized" housewarming party.
They'll have to limbo their way in while the jockeys will wonder why there's so much headroom. Averages can't encompass the range and diversity of a set of data points.
Don't even get me started on average grades. If Timmy gets all A's and Tommy gets all F's, the average grade is a C. But nobody in that class has a C! It's the mathematical equivalent of saying, "Well, it could be worse; at least you're not Tommy," to an honor student.
Averages sweep complexities under the rug. Tell someone that Earth's "average" temperature is around 15°C (59F). A Norwegian will laugh at you in the winter, and a Saudi Arabian will wonder what magical paradise you inhabit. Context matters!
Averages are like that cardboard-flavored rice cake of data representation—bland, unsatisfying, and telling only a fraction of the full rich story. But hey, at least they're easy to calculate!
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