Statistics can be misleading when they are presented without context about sample size, methodology, or the specific type of average used, as the same data can tell completely different stories depending on how it is framed.
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Huff: Lying with StatisticsAdded:
There's no joke that says there are three kinds of lies. There are lies, damned lies, and statistics. And in 1954, the journalist Darrell Huff wrote a book calling out all of the ways that people manipulate us using percentages, numbers, and statistics. Here are two examples. Suppose you read an advert for a toothpaste that says it reduces cavities by about 23%. That's impressive. It's a percentage wrapped in a scientific study, and we love those.
Except what you don't know is that this study is so small that the results are, statistically speaking, meaningless. If you repeated the same study 100 times, you would get different results. Except you pick the right study, you advertise it, and suddenly you have a fact. The statistic isn't false, per se, it's just a coin flipped dressed up as evidence.
Or take any headline that features the word average. Let's say you read about a community where the average salary is $50,000. That sounds like a comfortable and affluent place to live. But what you don't know is that figure is actually a mean where two millionaires in the neighborhood have skewed the result upwards. But the median, which is how most people are actually living, is far lower than that number. You have the same town, you have the same data, but they are wrapped in two completely different stories, depending on what average means.
The problem with numbers and statistics is that people tend to view them as being objective and unfakeable. But the problem is not with numbers in themselves. The problem is the stories that gave rise to them, and the humans that frame them.
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