Science: How data can be misinterpreted

Science: How data can be misinterpreted

Don’t take other people’s word for their conclusions – get the raw facts!

Recently you might have seen a bunch of headlines saying that since 1970, we have destroyed 60 per cent of the world’s wildlife. That’s a horrific thing to learn, and something requires immediate action. Either that, or collapsing backwards in your chair and giving up hope for the future.

But – and without making the story seem less important than it is – that 60 per cent figure isn’t actually correct. That’s not to say it’s wrong, but it’s been simplified. This article explains the difference in detail, but here’s a (long) quote, followed by some other ways data can be misused:

“…imagine you have three populations: 5000 lions, 500 tigers and 50 bears. Four decades later, you have just 4500 lions, 100 tigers, and five bears (oh my). Those three populations have declined by 10 per cent, 80 per cent and 90 per cent, respectively – which means an average decline of 60 per cent. But the total number of actual animals has gone down from 5550 to 4605, which is a decline of just 17 per cent.”

Things might be oversimplified

As you can see, when people report on research, they tend to grab for the most interesting and easily understood bit. That can mean discarding the context and some relevant information in favour of an attention-grabbing headline. This isn’t necessarily done with bad intentions, but it’s important to keep in mind when you read the latest science news… or a beauty product’s claims.

Or they might be overcomplicated

When people want to hide some results they don’t like, they might pile on a whole bunch of meaningless data to distract everyone. Again, the best way to get the real story is to sift through all that noise to see what the actual study is saying.

There isn’t enough data to back up the conclusions

If your 10-year-old cousin says he prefers the taste of Pepsi Max to Diet Coke, you can’t go out there and say every 10-year-old boy loves Pepsi Max. Well, you can, but you don’t have enough data to back that up. Now, if you ask 2000 boys his age and 1500 talk up Pepsi Max, you’re on more solid ground.

Something’s missing…

When you’re collecting data, it pays to be aware of the different variables at play. You might be ready to go public with your Pepsi Max results, but are those 1500 kids picking it because they really prefer the taste? Maybe Diet Coke isn’t sold in their town. Or Pepsi Max is cheaper, so they buy it more often. Maybe they think Diet Coke is for girls… In all these cases, taste is less of a factor in their decision.


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