From PhD comics
Weekend Moment of Zen 5-5-12
From PhD comics
Author: bs king
You are getting sleepy….
It’s been one of those weeks. I feel I would pay good money to be able to fast forward through tomorrow and jump straight to the weekend, as I’m pretty sure my brain is leaking out of my ear.
Given that, the headlines about this announcement by the CDC caught my eye. The headline reads “30% of US Workers Don’t Get Enough Sleep”.
Now, I’m in a pretty forgiving mood towards that sentiment. I’m tired today, and I know when I got in this morning most of my coworkers were dragging too. Any comment on sleep deprivation would have most certainly gotten lots of knowing looks and nods of commiseration. This study backs us up right? We’re all veeeeeeeeery sleepy.
Except that studies like this are almost all misleading.
Several years ago, I read a pretty good book by Laura Vanderkam called 168 Hours: You have more time than you think. It was through this book that I got introduced to the Bureau of Labor Statistics American Time Use Survey.
Now, most time use surveys….the type that people use to give reports about how much we sleep or work….are done by just asking people. Now that’s great, except that people are really terrible at reporting these things accurately. The ATUS however, actually walks people through their day rather than just have them guess at a number. It’s interesting how profound these differences can be. In another survey using time diary methodology, it was found that people claiming to work 60 – 64 hours per week actually averaged 44.2 hours of work. More here, if you’re interested.
Unsurprisingly, sleep is one area that people chronically underestimate how much they’re getting. The CDC study, which it admits was all data from calling up and asking people “how many hours of sleep do you get on average?” found that 30% of workers sleep fewer than 6 hours per night. The ATUS however, finds that the average American sleeps 8.38 hours per night….and that’s on weekday nights alone. Weekends and holidays, we go up to 9.34.
I couldn’t find the distribution for this chart, but I did find the age breakdown, so we can throw out those 15-24 and those over 65 (all of whom get about 9 hours of sleep/night). We’re left with those 25 – 65 who average roughly around 8.3 hours of sleep per night.
Alright, now lets check the CDC number and figure out how much sleep the other 70% of the population would have to be getting in order to make these two number work.
If we take some variables:
a = percent of people sleeping an average of fewer than 6 hours per night
x = the maximum number of hours to qualify as “fewer than 6 hours”
b = percent of people sleeping more than 6 hours per night
y = average amount they are sleeping to balance out the other group
c = average amount of sleep among workers according to the ATUS survey
We get this: ax + by = c
And then substituting: (0.3*5.9) + (0.7*y) = 8.3
Solving for y: y = 9.33 hours of sleep per night
Are 70% of Americans of working age actually getting 9.33 hours of sleep per night? That would be pretty impressive. It would also mean that instead of a normal distribution of sleep hours, we’d actually have a bimodal distribution….which would be a little strange.
There is, of course, the caveat that those answering the ATUS represent the whole population while the CDC targeted working adults. It’s a little tough figuring out how profoundly this would affect the numbers since the BLS reports workforce participation rates for those 16 and up. The unemployment rate for 2010 (the year the survey was completed) hovered just under 10%, but the “not in labor force” numbers are a little harder to get without skewing by the under 25 or over 65 crowd. The CDC also didn’t report an average, so I can’t compare the two….but given the 30% number, the six 6 hours or less would be less than half a standard deviation from the mean (if the sleep data was roughly normal).
So does this mean I’m not as tired as I think I am? Nope, I’m pretty sure I’m still going to bed early tonight. I will however, be aware that a tiring week does not necessarily mean a sleep deprived one.
Hey, at least someone’s thinking
Best idea I’ve seen all day….people taking Congress to task for having no system for vetting scientific testimony. (H/T to Maggie’s Farm)
Apparently what sent them over the edge was when a scientist misquoted his own paper during testimony, skewing his own research. Yikes.
One of the authors website is here….haven’t had time to look around much.
Everybody loves a (certain sort of) hypocrite
Last week I posted my annoyance at studies that put more work in to proving that substitute a potential proximal cause for the real issue without adequately proving that was a valid substitution. At the time I was talking about food deserts, but today I found another great example. A study that has gone viral links homophobic behavior with secret homosexual desires.
Now, when I first heard these results in passing, I was pretty surprised. I spent years in a Baptist school with plenty of people who were quite clear about their homophobia, and I have always thought it overly simplistic when people say that’s all repressed homosexuality. I think the reasons behind any prejudice are likely to be complicated and multifaceted. Plus, the logic seemed pretty sensationalistic…..and after all, we don’t accuse misogynists of wanting to be women.
Anyway, I hadn’t had time to look in to this study, but I ran across this takedown by Daniel Engber on Slate today. I thoroughly enjoyed the article (and extra credit to Slate for not being 100% PC). The author points out that the results of this study are only as trustworthy as the semantic association method (the implicit association test) they used to prove it. This technique, which essentially involves showing a subliminal message followed by a picture, can be questionable. From the Slate article:
Should we trust this interpretation of the data? In the Times op-ed, the authors claim that the reaction-time task “reliably distinguishes between self-identified straight individuals and those who self-identify as lesbian, gay or bisexual.” Their formal write-up of the work for the Journal of Personality and Social Psychology is a bit less sanguine on the method, citing just one other study that has used this approach, and saying it “showed moderate correspondence with participants’ self-reported sexual orientation.”
So there’s that.
The other issue that Engber didn’t mention is that this study was performed on college freshmen. I REALLY hate when people generalize from that age group because….stop me if I’m getting crazy here…I am pretty sure kids that age have a less well developed sense of identity than the adult population at large.
Even if the data were 100% accurate, I think that the youngness of this sample would skew the results. At least when I went to college, quite a few kids came out during that time, and it was a time of questioning identity for pretty much anyone. According to the best research I could find, the average gay person doesn’t even self-identify as gay until 16, and the majority of people come out either in college or after developing an independent life. So the chances that expressions of sexual identity, especially subconscious expressions, may look different at 18-20 is pretty well supported.
Now I’m pretty sure there will always be Ted Haggard’s or Larry Craig’s in this world…just like there will always be John Edwards or Elliot Spitzer’s. Sex, gay or straight, will always capture headlines more than boring things like tax evasion, even though they are both hypocritical. Still, with studies like this, I urge caution. Accepting the result means accepting that words on a screen and hundreths of a second of reaction time can accurately capture homophobia, and that a 19 year olds perspective on the world can translate to all adults. If you believe both of those, then go ahead and quote the study. Otherwise, you may want to hold your judgement for a bit longer.
Never trust an infographic over 30
I’ve been tinkering with improving my data visualization skills recently, as I’m sick of using nothing but Excel (although if you want to continue using Excel for everything, this is a pretty useful website).
As anyone who takes a look around the interweb can tell you though, there is a pretty insidious type of data visualization that’s been flooding our society.
Oh yes, I’m talking about the infographic.
While sometimes these are endearing and amusing, they are often terrible, misleading and ridiculous. I was going to formulate some thoughts on why they were terrible, and then I found out that Megan McArdle already had in a column for the Atlanic. It’s a pretty good read with lots of pictures. Her summation at the end pretty much says it all:
If you look at these lovely, lying infographics, you will notice that they tend to have a few things in common:
- They are made by random sites without particularly obvious connection to the subject matter. Why is Creditloan.com making an infographic about the hourly workweek?
- Those sites, when examined, either have virtually no content at all, or are for things like debt consolidation–industries with low reputation where brand recognition, if it exists at all, is probably mostly negative.
- The sources for the data, if they are provided at all, tend to be in very small type at the bottom of the graphic, and instead of easy-to-type names of reports, they provide hard-to-type URLs which basically defeat all but the most determined checkers.
- The infographics tend to suggest that SOMETHING TERRIBLE IS HAPPENING IN THE US RIGHT NOW!!! the better to trigger your panic button and get you to spread the bad news BEFORE IT’S TOO LATE!
If that’s too many words for you though, she also includes this graphic:
So while the infographic can be quite useful when tamed and sedated, if you meet one in the wild, be very very careful. Do not approach directly, do not look it in they eye.
Friends don’t let friends use lousy infographics (I’m looking at you facebook).
Friends don’t let friends use lousy infographics (I’m looking at you facebook).
Weekend Moment of Zen 4-29-12
Since my mother still doesn’t agree with any of my food desert postings, I thought of this comic.
Mom, I think we should consider that maybe obesity causes food deserts. Think about I’m pretty sure I heard about obesity before I heard the phrase food desert. I’m pretty sure that proves something.
Circumventing the Middle Man
Well, my post on justifiable skepticism (Paranoia is just good sense if people actually are out to get you) certainly was the big winner for traffic/comments this week. I was happy to see that…I had a lot of fun putting that graph together and thought the outcomes were pretty striking. Thanks to Maggie’s Farm for linking to it.
It was my post on food deserts however, that got me the most IRL comments. Both my mother and my brother commented on it, and not terrifically positively. In retrospect, I wasn’t very clear about the points I was trying to make, though to be fair I had spent a lot of the day on an airplane.
My issue with food desert research, or any similar research, is that what we’re really talking about is a proposed proximate cause to a larger issue: obesity. In my experience, just having people tell you why they think something’s happening, isn’t good enough to prove that’s the actual reason. Thus my quibble with much of the theorizing about obesity problems….you have to make sure that what you’re theorizing is the cause is actually the cause (or one of the causes) before you start dumping money in to it. You cannot make the middle man the holy grail if you haven’t established that it’s really a cause.
Unfortunately, people love to jump on good ideas before truly establishing this link.
Example: A few years ago, it was discovered that 22% of school children were eating vending machine food. This school had an obesity problem, the food in the vending machines was unhealthy, so a push began to remove vending machines from schools. Schools balked, as they make money from vending machines, but the well being of children came first…..until of course this study came out proving that reducing access to vending machines didn’t actually effect obesity rates. Oops.
It’s really a simple logic exercise…proving that kids are (a) obese and (b) eating from vending machines does not actually prove that getting rid of (b) will reduce (a).
That’s why I liked the research in to the difference food deserts make in obesity. It’s a question that needs to be asked more often when trying to address a large issue: are we sure that the issue we’re trying to address will actually help the issue we were concerned about it the first place???
If you haven’t established that it will, then be careful with how you proceed. Addressing food deserts (or vending machines or whatever) is a means to an end, and you shouldn’t confuse it with the end itself…unless you have really good data backing you up.
Trillion Dollar Debt Day
Bias alert: I graduated college with a LOT of debt. It was nearly ten years ago, but I was still far above the current average widely reported in the media. In 3 years, I had paid off all but one loan that was locked at 2.3% interest. I paid that off two years later due to the fact that Sallie Mae is an absurdly evil company and I was sick of dealing with them. All in all, I was debt free 20 years earlier than projected and today have zero debt from either my bachelor’s or master’s degree.
Now, all that being said, I guess I can’t feel too left out that I didn’t get invited to the student protest that was Trillion Dollar Debt Day. Apparently yesterday was the day that total student loan debt in this country hit $1,000,000,000,000. Want to see it in real time? Here you go:
http://www.finaid.org/loans/studentloandebtclock.html
Anyway, student debt is a complicated issue with lots of statistics ripe for dissection. Actually, the debt really isn’t that complicated….it’s there because college costs have gone up far more than average household income has, and more people are going for both grad and undergrad degrees. What’s complicated is how people interpret what to do with these statistics. For example (from the clock website above): “Student loan debt, on the other hand, as been growing steadily because need-based grants have not been keeping pace with increases in college costs.” Not hard to see what that websites solution would be to this issue.
The 1 trillion number is impressive, but it is not often mentioned how heavily the increase in debt level correlates with how sharply the number of students have gone up. According to the National Center for Education Statistics “enrollment in degree-granting postsecondary institutions increased by 9 percent between 1989 and 1999. Between 1999 and 2009, enrollment increased 38 percent, from 14.8 million to 20.4 million.” Nearly 6 million people extra people in 10 years, combined with rising costs and a recession…that will make that number shoot up in a hurry.
In the past 5 years, the average debt per graduating college student (bachelor’s level) has only gone up by about $4000, unadjusted, or $2500 in adjusted dollars.
| Year | Average Debt | Average Debt (2010 $) | Median Earnings | Median Earnings (2010 $) | Debt:Earnings (inflation-adjusted) |
|---|---|---|---|---|---|
| 2006 | $21,100 | $22,822 | $45,221 | $48,912 | 0.47 |
| 2007 | 21,900 | 23,032 | 46,805 | 49,224 | 0.47 |
| 2008 | 23,200 | 23,497 | 47,094 | 47,696 | 0.49 |
| 2009 | 24,000 | 24,394 | 47,510 | 48,289 | 0.51 |
| 2010 | 25,250 | 25,250 | 47,422 | 47,422 | 0.53 |
Sources: Project on Student Debt, U.S. Census American Community Surveys (1-year estimates, 2006-2010), Bureau of Labor Statistics CPI Inflation Calculator.
You multiply even that amount over 20.4 million however, and the levels start reaching crisis proportion. Additionally, these “average” numbers, while reported very exactly, are all self reported by the schools. Also, out of the 2,300 schools they asked, 500 were tossed for identification reasons, and about 300 just didn’t report anything. This makes these numbers highly suspect.
Overall, I’m not saying there’s not a crisis. I work in health care, and it’s totally ludicrous to me that while we’re all scrambling to cut costs as fast as we can, higher education is not doing the same. I’ve also had a mortgage for nearly as long as I had my student loans, and I can tell you that my mortgage company has not once pulled any of the disgusting shenanigans that Sallie Mae pulled with my student loans. I used to have to save my receipts because they, I kid you not, used to ADD small amounts of money to my balance at random. I would then have to spend 45 minutes on the phone with them proving that this had happened. I was always right, they would merely “apologize for the misunderstanding”.
However, with this issue, as with so many others, watch the numbers when emotions run high. People love to throw data at others in these moments, knowing it won’t be questioned. Business Insider, for example, claims that “For many of you, your degrees won’t matter. One-third of you will land full-time jobs that don’t require them.” They don’t mention that’s 33% of 500 people who just graduated. Check back in 5 years, BI, then show me the numbers.
Begin with the end in mind
Most of what I do all day is in the loose category known as operations research. This is an interesting sort of research that typically starts with a question, and then involves gathering qualitative and quantitative data until you get a hypothesis. Adjustments are made until you get going in the right direction, which is normally related to either getting more of a good thing or less of a bad thing…or often both.
This is my favorite type of research for any field for a variety of reasons: it’s practical, it helps people, it tends to cut through feelings and deals with facts, and it leaves room for people to be surprised.
The downside is that the questions are often complex and the answers multi-dimensional. That’s why good research of this kind is so darn impressive. I read a great article today about Jacqueline Campbell and her work to reduce domestic homicide. She started with a complex problem, and worked both forward and backwards until she came up with something that worked. Working backwards, she went deep in to the statistics to figure out which situations were the most likely to result in homicide, and then trained the front end responders how to reach out to those who were at the most risk. While she will not claim credit, it is noted that the state where she implemented this program (Maryland) has cut their domestic homicide rate in half.
Domestic violence is an issue that can very easily get mired down in politics and emotion, so it’s interesting to note that this is one of the few programs that is getting bipartisan support. That’s such a good outcome when somebody actually pragmatically addresses an issue rather than just catering to their own pet theories.
To note: starting research with a goal in mind is beneficial only when it’s not a guise to push an agenda. It’s only good if you really don’t know how to get there. I feel this is research at it’s best, research that actually helps a real world problem. I have nothing against research that helps us see the world in new ways, but my practicality bias is probably why I did engineering and not theoretical physics. It takes all types, I just wish more would focus on the “how do we get there” type questions.
The rise of the datasexual
Datasexual…apparently it’s a thing.
Sometimes I worry that’s what I might become…obsessed with my own personal data, quantifying myself until there’s nothing left that can’t be counted. I already have an embarrassing number of spreadsheets in google docs dedicated to tracking all sorts of things in my life….7 I’m currently updating regularly.
Normally, my love for efficiency saves me though. In healthcare, there’s a pretty unending stream of data, so we’ve had to learn how to sort through to what’s useful. If you don’t know how you’ll use it immediately, or at least have a very large hunch, we don’t collect it.
If efficiency doesn’t work as a motivator, I figure that’s a sign I need to get outside. Good thing I have a dog to remind me to do that.
In case you’re curious, on a sunny day like today, he’ll walk for an average of 24.6 minutes, with a standard deviation of 3.3, highly dependent on whether or not we see the UPS guy go by. He HATES the UPS guy.
graph paper diaries 