Science Isn't Broken | FiveThirtyEight - 0 views
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If we’re going to rely on science as a means for reaching the truth — and it’s still the best tool we have — it’s important that we understand and respect just how difficult it is to get a rigorous result
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Scientists’ overreliance on p-values has led at least one journal to decide it has had enough of them. In February, Basic and Applied Social Psychology announced that it will no longer publish p-values.
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P-hacking and similar types of manipulations often arise from human biases. “You can do it in unconscious ways — I’ve done it in unconscious ways,” Simonsohn said. “You really believe your hypothesis and you get the data and there’s ambiguity about how to analyze it.” When the first analysis you try doesn’t spit out the result you want, you keep trying until you find one that does.
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Science isn’t broken, nor is it untrustworthy. It’s just more difficult than most of us realize. We can apply more scrutiny to study designs and require more careful statistics and analytic methods, but that’s only a partial solution. To make science more reliable, we need to adjust our expectations of it.
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From 2001 to 2009, the number of retractions issued in the scientific literature rose tenfold. It remains a matter of debate whether that’s because misconduct is increasing or is just easier to root out.
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Science is not a magic wand that turns everything it touches to truth. Instead, “science operates as a procedure of uncertainty reduction,” said Nosek, of the Center for Open Science. “The goal is to get less wrong over time.”
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Some of these biases are helpful, at least to a point. Take, for instance, naive realism — the idea that whatever belief you hold, you believe it because it’s true. This mindset is almost essential for doing science, quantum mechanics researcher Seth Lloyd of MIT told me. “You have to believe that whatever you’re working on right now is the solution to give you the energy and passion you need to work.” But hypotheses are usually incorrect, and when results overturn a beloved idea, a researcher must learn from the experience and keep, as Lloyd described it, “the hopeful notion that, ‘OK, maybe that idea wasn’t right, but this next one will be.’”