One was made up. All three are the kind of thing you might act on. Pick the fake.
Notice how little the fake had to change to pass. That's the trick: a false claim borrows the shape of a true one — a plausible source, a confident number, a rule that sounds like it must exist. The cost isn't being wrong in a quiz. It's the decision you make afterwards.
It doesn't stop on its own. Someone has to ask: says who?
A statistic is a number that's meant to represent a group of people. They can be important and useful, but are easy to misinterpret and use maliciously. Here's how to spot a stat that has some credibility to it, and how a bad one can become harmful.
Every stat takes a whole crowd of people and mashes them into one figure. If done well, it can act as a fair summary. But if lazily created, it can become a huge misinterpretation.
So don't start with "what's the number." Start with "how was the number determined."
Ask four people how tall they are and you might get a completely different data set than if you asked four hundred. A small sample set isn't lying, it just doesn't speak for everyone.
And if a stat won't tell you how many people it's based on, that's usually because the answer would affect your perception of it.
If you wanted to figure out the most well-percieved phone, you wouldn't exactly only collect data from Apple Store customers. Many sampling biases exist, and all of them can affect a statistic's accuracy.
A solid poll pulls a random mix of the whole group. Focusing on a smaller collection within that group doesn't allow you to connect it to other people.
Ice cream sales and shark attacks both go up at the same time every year, but they aren't exactly correlated in any way. When you don't consider confounding variables, like seasonal trends, your data can become more of a conspiracy theory than an actual connection.
So when you hear "X is linked to Y," stop and ask what else might explain it.
The same two numbers, 49 and 51, can look like a marginal gap or a small difference depending on where the bottom of the chart sits. Start the axis near the top instead of at zero and a tiny gap suddenly looks like a cliff.
Before you panic at a dramatic bar chart, look at the numbers running up the side. Half the time the picture is doing all the work.
A "100% increase" might just be a disease going from 1 case to 2. Percentages leave out the starting number for a reason. "Up 100%" makes people nervous. "One more case than last year" doesn't.
Whenever you see a big percent, check for the actual count. Out of how many? Up from what?
Untrue statements can quickly become malicious. There doesn't need to be substantial proof for a claim to be widely believed.
A shaky stat is where a lot of stereotypes borrow their fake credibility. "It's not prejudice, it's statistics" only works if nobody bothers to check the statistics.
This doesn't mean every number is out to get you. Good statistics are one of the best tools we've got for actually understanding stuff. Just be aware of how a small error in a study can produce a completely innacurate result.