Alright, so you have a scale that looks like this:
Uncategorized
Who needs facts when I got my gut?
When I get in to arguments with people about data, most of the conversation is pretty predictable. Sometimes people counter with contradictory data, claim my data is biased, is from a bad source, is outdated, irrelevant, or otherwise not worthy of consideration. I can accept this.
And this little elite stayed home….
I’m catching up on my reading after a week of under-connectivity, and I was interested to see this piece linked to from the AVI’s site. It’s about a recently published paper comparing the rates of “opting out” of the workforce for mothers who graduated from elite vs non elite institutions. Apparently the better the school you went to, the more likely you are to stay home with your kids.
But as soon as Hersh separates out women with children from those without, it becomes obvious that women from tier 1 schools are significantly more likely to be home with the kids than the others — 68% of mothers from the tier 1 schools were employed, compared to 76% of those from the other schools.
Sounds straightforward right? 8% more women from elite schools are home when their kids are young as opposed to everyone else. Well, lets see what the actual paper said:
The employment rate for married mothers with children who are graduates of the most selective colleges is 68 percent, in contrast to an employment rate of 76 percent of those who are graduates of less selective colleges.
Pretty much the same thing right? I mean, if you were to just read that second statement, you’d think the first one paraphrased it pretty well. But when I looked at the data tables, that’s not what it said. The 68%-76% jump is not between elite schools and everyone else, but between elite schools and tier 4 schools. Here are the numbers (page 50 of the pdf from the link above):
Tier 1 Tier 2 Tier 3 Tier 4
Children 67.7 71.9 71.6 76.3
No Children 87.9 90.9 89.6 89.8
I tried to parse through the methodology for assigning tiers, but honestly I got confused. It seems to be a mash up between Carnegie ratings and Barron’s. In other words, the categories may not necessarily mean what you think they mean. It seems private research I and II universities were considered tier 1, private liberal arts colleges are tier 2, public research universities are tier 3, and all others are tier 4. This would put my alma mater as tier 1, and I would hardly consider it “elite”.
Anyway, there’s some good commentary going on about this article, but I thought the exact definitions being used were interesting. I think it is interesting to see how people behave when they have money vs when they don’t. Also, I thought it was equally interesting that much of the difference came from women who had earned degrees in law or MBAs. These women quite their jobs at much higher rates than those with MDs or teachers. It struck me as interesting because people do not generally love business or law the way people love medicine or teaching. It seems to me that this data suggests that when women have their druthers, they keep jobs they love, and ditch jobs that are more status driven.
Moral of the story: find a job you love, and always read the data tables.
You can say this about life…it goes on
Well, it’s been quite the week here at Bad Data Bad.
Lt James Clark, RIP
Wednesday Brain Teaser 4-10-13
Apologies in advance, but this has nothing to do with math…but I thought it was fun, so it’s going up.
Do scientists need math?
I was exactly one sentence in to this Wall Street Journal article about how you don’t need math to do science when I thought “huh, I bet this guy’s a biologist”. I was right.
EO Wilson is a Harvard biologist/naturalist who leads the world in the study of ants, and he wants people to know that you don’t need math to be a scientist. Now this is a good point. From the acronym STEM to the more colloquial ways of referring to geeks, we tend to conflate being good at math with being good at science and vice versa. For some sciences, there really is not a good reason to do this.
On the other hand, I’m not sure I loved the execution in this article. A few things about this:
- What seems to annoy Wilson most is calculus requirements. I won’t quibble with him on that. However, I think a basic understanding of statistics is critical for any scientist…otherwise how will you read/interpret nearly any paper in your field? Statistics is often lumped in with math, so I would have liked to hear his thoughts on this.
- As so often happens, Wilson left the entire field of medicine out of his discussion about science. Walk in to any group of freshmen bio majors, and you’ll find a huge percentage of them are pre-med. Many med schools require math/stats classes for admission. That’s a big reason why these kids are taking math classes to begin with.
- It’s not until paragraph 11 that Wilson mentions that if you’re bad at math, you should pretty much stay away from chemistry and physics. So while the headline says “scientists don’t need math” what he means is “some types of biologist don’t need math”.
- He estimates that only 10% of mathematical models of biological phenomena hold any water. Given my blog posts last week, I thought that was really interesting.
Kill your television
I saw an interesting headline today: “Broadcasters Worry about ‘Zero TV’ homes”. At first, this confused me…why was “Zero TV” in quotes? Is this some new grammar issue I’m not aware of?
So despite my better judgement, I decided to read the article. I discovered that “Zero TV” does not, in fact, mean a house with zero TVs. Apparently it’s a marketing category for people who don’t pay for cable, satellite TV, or a digital antenna. Thus, they can own a TV, but must use it in a “non-traditional” way…like for watching movies on DVD or streaming online or something.
I was pretty disappointed by that definition. I mean, when I think of using a TV in a non-traditional way, I think of things like this:
or this:
But using a TV for watching movies or shows that you’re downloading or streaming as opposed to buying cable? That’s hardly avant garde.
Also, anyone with a TV, should not be called “zero TV”. That’s just annoying.
I was, however, happy to find out that the Nielsen Company apparently has a “Senior Vice President of Insights”. That manages to sound both pretentious and like something out of a cartoon all at the same time.
I like it.
Friday Fun Links 4-5-13
I have a very narrow taste in April Fools Day jokes. I don’t like jokes that attempt to humiliate others for laughs, make people looks stupid, etc. I do however, like a good kitty in a backpack joke.
If you can’t out run them, take a cab. Here’s a visual of how cab drivers earn their money.
For your education this week: 7 misused science words.
Now just for the hell of it, infomercial gifs. I kind of really love gifs.

