There are happy reasons to be up past midnight --star watching, seduction, sentient computer program completion. But I spent my senior year living at the Bridge Peer Counseling Center, where from midnight to 9 AM I took calls from anyone who needed to talk. And while some of those calls came from sleepy people who just wanted to talk about their dreams, in general I grew to suspect that being awake at 3 AM is not correlated with high life satisfaction.
At 23andMe, I confirmed this suspicion, as a post on the company's blog, the Spittoon [1], describes. Customers at 23andMe answer questions about everything from extroversion to earwax -- it's without a doubt the most beautiful dataset I've ever gotten to work with -- and we track what time every answer comes in. So I decided to look at how traits varied as a function of time, and lo and behold...
If you're on a computer answering survey questions at 3 AM, you're probably not a happy bunny. You're also disproportionately likely to suffer from mania. And unsurprisingly...
You're much less likely to have children. You're also more likely to be male [2].
So all of these are pretty terrible (especially the last one!); maybe you should go to bed on time. (And don't give me any arguments about correlation not implying causation; I don't discuss statistics with the sleep-deprived [3].)
Funnily enough, when I started this project, I wasn't looking for sad sleepless people at all: I was looking for happy holiday people. I was lying in bed the day after Christmas feeling full and content, and I thought perhaps I would be able to see a bump in people's BMIs in the weeks after the holidays. Maybe it would be smaller for Jewish customers, or atheists, over Christmas? Would we see a change in political views over 4th of July weekend?
But none of these holiday effects turn up in our data at all. Which drives home a lesson I've learned repeatedly: often, the gold in the data isn’t where you expected it to be. To a statistician, a sad sleepless person is just as good as a happy holiday person, as long as both are statistically anomalous.
Sometimes I take a break from being a statistician to become a human being, however, and so if you ever happen to be sad and sleepless, you can give the Bridge a call at 650-723-3392: they're free, anonymous, and always around. They're also a lot less cranky, on average, now that I'm no longer answering the phone.
I've been talking to eHarmony's scientists about their data, so we'll return to less depressing topics soon (probably in posts that are both shorter and more frequent.)
Notes:
[1] Because you have to spit into a tube to get your DNA tested.
[2] One might wonder if all the other effects are simply a result of the gender difference, but that doesn't suffice to explain them.
[3] Obviously, we can't infer causation here. But in general, there's substantial evidence linking sleep deprivation and depression. Addendum: Maria Mateen, a psychology researcher, tells me that abnormal sleep patterns are actually one of the diagnostic criteria for mania, as well as for other psychological disorders.
Hi Emma,
ReplyDelete1) How did you investigate whether or not gender can explain the other effects as you noted in footnote #2?
My guess: Use logistic regression with gender as the target variable and the other effects as predictors. However, that would not take the dependence on time into account. Perhaps you used some type of regression in functional data analysis, with gender as a time-independent binary target and the other effects as time-dependent predictors. Your clarification on this would be much appreciated.
2) My goodness - how did you sleep in your senior year with your 12-9 am volunteering while finishing your B.Sc. and M.Sc. at the same time?
As always, it's a pleasure to read your work!
Eric Cai
The Chemical Statistician
http://chemicalstatistician.wordpress.com/
@chemstateric
https://twitter.com/chemstateric
Youtube Channel:
https://www.youtube.com/user/ChemicalStatistician/videos
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