Only two remained: Leo with a tendency for intestinal bleeding, and Sagittarius with a risk of breaking the upper arm bone. But those two are well within the recognized margin of error for a study with so many variables.
"All 24 disappear," Austin says.
So there is no connection between astrological signs and health, despite the fact that a huge sample indicated there was. The second sample, called the validation sample, blew it away.
Austin says this isn't just a problem for scientists. We all engage in data mining from time to time.
"If you look at enough clouds, eventually one of them is going to look like a dog chasing a cat," he says. "It's not really a dog chasing a cat. It's a random, atmospheric pattern. But if you look at enough clouds you're going to see a dog and a cat.
"We tend to impose patterns," he adds. "People do it with their horoscopes. They remember the one that came true, but they don't remember all the times that it didn't. They conveniently forget all the times that there wasn't a pattern."
Austin presented his study during the recent meeting of the American Association for the Advancement of Science in San Francisco, and he had a word of advice for his fellow scientists.
Don't believe your own findings until they are validated by someone else using a different method.
And as a statistician, he warns that asking too many questions of the data increases the risk of error. In seeking 24 reasons for hospitalization he was asking 24 questions. That gave him "a 71 percent chance of mistakenly concluding one association that doesn't exist," he says.
That huge error rate is what allowed him to disregard Leo and Sagittarius, the only two that showed up in the second sample.
Personally, I'm glad. As a Gemini, I don't want to wake up every morning with a hangover.