Lt James Clark, RIP

It is with tear filled eyes and a heavy heart that I write this post.  On Thursday, April 11th, 2013, my uncle, Lt James Clark of the Bedford NH Fire Department, was found dead in home. He was 56 years old.
Jim was my uncle, my mother’s best friend and our neighbor for 25 years.  The space he leaves behind is large and will not be easily filled.  Words cannot express how unfair or untimely this death is.  He died of a massive heart attack shortly after getting home from a busy shift at the fire station, and was found by his 16 year old daughter.  Based on the coroner’s findings, it has been ruled that it was likely his work is what triggered the heart attack, and he is considered to have died in the line of duty.
On Tuesday, I will attend my first fireman’s funeral.  Because he is considered to have died serving, the funeral will most likely be the most elaborate I have ever attended.  This is ironic, as he was the most humble man I have ever met.
I’m posting this here for two reasons.  First, I wanted to give an explanation for the lack of posts over the last few days, and why they may be spotty in the days ahead.  Second, I wanted to share some thoughts on intellect and how we judge it.
There are two ways of judging the intelligence of another person.  The first is to sit someone down with a well designed test and to see how they do.  Depending on the test, this should give you some sense of intellect.  The second, more common way, is the assessments we make about those we meet when we don’t have a test on hand and have to rely on our own senses and their accuracy.  While this is what we are called on to do most often, our assessments here often have more to do with us than with the person we are assessing.
My uncle was the one who taught me the utter fallibility of my own sense of other people’s intelligence.  He was a man who was too often typecast: he was a farmer, a fireman and a runner.  He was who you called on when you needed wood chopped, a fence mended, or to borrow a truck.  He was a true Yankee: thrifty, hard-working, reserved, but kind. In crowds, he would let himself fade to the sides, too often marginalized by our societies obsession with degrees and it’s frequent perception of both conservatives and country dwellers as lesser minds.  This stereotype is wrong.
My uncle was in possession of one of the rarest and most amazing minds of anyone I have ever met. He communed with animals and the land as though he were made of more primal stuff than the rest of us.  He was the type of man who can look at the sky and tell you if the weather’s good for haying, or identify which chicken is laying the good eggs.  He read widely about history, politics, philosophy and poetry.  He could converse easily on the intricacies of the Affordable Care Act, and ruminate about the nature of God and life in a way very few could.  He was not a numbers guy, but he had a keen sniff test.  He was the sort of guy who could hear of a study and just say “something’s not right”.  His sense was always spot on.  He was a painter, and he left behind a treasure trove of watercolors of the farm he worked and the land he loved.  He was a poet, and had put together a full volume of his work in the year before his death.  
As people filed in and out of my parents house for the last few days, it’s become clear how few people knew how much was going on in his head.  The most common phrase in our house these days seems to be “I never knew Jim did ______”.   In a world obsessed with status and accolades, my uncle never offered more than he was asked, never asked for credit if it wasn’t offered.  He taught me that the musings of a man after a few hours on a tractor can be more interesting than those of someone locked in an ivory tower for years, and that the farmer philosopher is not limited to characters in a Robert Frost poem.  
So I’ll miss you Uncle Jim.  I never told you that you changed the way I speak to people, that you made me slower to judge, more eager to listen, and reminded me that still waters run deep.  I’m sorry that too often when we talked I got hung up on proving how smart I was instead of taking advantage of the time I had to hear how smart you were.  I’m sorry you had to go so soon, and I hope that you are in a great field in the sky, where the weather’s always right for haying and the baler never breaks down.
Rest in peace.

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.

This mental floss link gives you 8 minutes to name as many of the 43 presidents as you can.
I got all but 12….apparently my memory cuts out in 1881 and picks back up in 1933.  It’s one of those tricky things where you flat out can’t remember some, can’t believe you never entered others, and kick yourself for at least one or two.  I’m not naming names because I don’t want to skew your results…because of course we need a poll here:

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:

  1. 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.
  2. 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.
  3. 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”.
  4. 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.  
Overall, I actually ended up agreeing with Wilson quite a bit, the caveats above notwithstanding.  Making science accessible only to those who pass several bars of intelligence is a bad move.  However, I did have to wonder if he view was skewed just a bit by being at Harvard.  I mean, how many people get in to Harvard every year who are truly bad at math?  Harvard has had a grade inflation problem for years, and it’s no surprise to me that people migrate out of subjects where the grading is harder/more objective to those subjects where the grading is more subjective.  I have friends who went to Harvard.  I’ve seen this happen.  
It may be a nice thing to tell your professor “I’m scared of math” but how many really meant “I got a C in that, but an A in my psych class?”  A sense of wonder and curiosity about the world is wonderful, a fear of challenging yourself and failure is not.  
I guess what I’m saying is, I’d like to see some data on this before I buy this explanation.  

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.

Who pays for daycare?  This article covers the issue of headlines that state that the cost of childcare is a mother’s problem/women’s problem.  Kudos for mentioning that this leaves dads out of the picture.  Language matters, give fathers their due!
With all the de-extinction talk lately, I think we need to ponder this article.  Could you outrun a t rex?

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.

Wednesday Brain Teaser 4-3-13

This is one of the more interesting puzzles I’ve seen in a bit.  I liked it.  Also, I put up the rationale for the second answer to last weeks problem in the comments section there.  

Alright, read this left to right, top to bottom, and tell me what the next two rows are (the question marks show the current number of numbers for the missing rows:

       1
1 1
2 1
1 2 1 1
1 1 1 2 2 1
? ? ? ? ? ?
? ? ? ? ? ? ? ?

Sex, models and housework

Sorry, not sex with models (or models doing housework) but mathematical models about sex and housework.  The first study I wanted to look at in my discussion of the use of models in data reporting actually got sent to me a while ago.  The headlines around this were things like “Want to have more sex?  Men, stop helping with the chores!“, and a concerned (male) reader sent me the link with a “what’s up with this???”.

Essentially, the study took answers from a large survey that asked people about their household division of labor, their marriages in general, and their sexual frequency.  The authors were attempting to prove or disprove several notions about how housework and sex relate in marriage. They came to the conclusion that the more housework conformed to traditional gender roles, the more sex was had by all.  A few notes about the study up front:

  1. The data was collected in 1992, with a mean age of 43 for women/46 for men.  This is notable because people’s expectations for marriage have change dramatically over the past few decades (divorce rates peaked in the 80s), so the generalizability may be limited.  However, this data set was used because it’s the largest in existence that has all this information.  The authors acknowledge this limitation.
  2. The authors divided chores in to traditionally female (core) and traditionally male (non-core) tasks.  Core tasks include meal prep, cleaning, grocery shopping, etc and non-core tasks include lawn maintenance, bill paying and driving.  The finding was that the more men did the core work, the less sex the couples had, but the more non-core work they did, the more sex they had:So the headlines that more chores = no sex are wrong…it was the “wrong” kind of chores that influenced things.
  3. The authors never studied (nor claimed to study) the effects of changing chore arrangements on sexual frequency.  In fact all of their conclusions are based on the entire marital arrangement, so do NOT take the headline writers advice and start shaking things up assuming that this will have a particular result.  
  4. I found it fascinating that the authors specifically ruled out coercion as a factor here.  Satisfaction was fairly high across the board. 
  5. As the data is presented here, I do not argue with their conclusion.  While I think we could all quibble about the mechanism that causes this to be true, the data as presented in the paper supports what they say it does.
Getting back to the modelling stuff….the graph above shows the model they came up with, after controlling for all other factors.  Kind of nifty, right?  But what concerns me about this is that it’s so nice and linear.  When I look at graphs that are supposed to model certain phenomena, I take a look at the extremes.  Now, I know quite a few super-egalitarian couples, but I actually don’t know any couple in which the male does 100% of the cooking, cleaning, laundry, etc.  Even with over 4000 couples in this survey, how many did they really have at that end?  What would cause that arrangement to evolve?  Unemployment? Disability? I would be very suspicious that any couple would actually settle in to that arrangement long term…so I’d wonder how things would really behave at that end of the chart.  
Another note on this model: the key phrase is “controlling for all factors”.  From a research perspective, the researchers appear to have done this quite diligently.  From a real life perspective though, people attempting to extrapolate this data for their own lives would do well to remember we don’t live in vacuums (no pun intended).  Spending time with your spouse, having a higher income, not having small children, and being religious all are positively correlated with higher sexual frequency.  When I was researching this article, I was interested to find that the WSJ had taken a different tactic with their article, and mentioned that those who do more total chores also have more total sex.  Work hard, play hard they called it.
Finally, we have to consider why the researchers likely went with a mathematical model at all over just reporting the data directly.  My guess is outliers.  When I followed up with the guy who sent me the study, I mentioned that it was key to remember that this was not a straight up reporting of data, but rather an extrapolated model.  He asked why they would do that.  The only response I could think of is that it’s likely the data simply wasn’t this clean when they put it together the other way.   That doesn’t mean the conclusions are wrong, it just mean the reporting isn’t quite as direct as we might presume from the headlines.  
Blame the journalist.

Now if you’ll excuse me, I have to go do some dishes.

Church attendance and predictive models

Happy Easter, to those of you who celebrate!

I did in fact make it to church this morning, which weirdly enough got me pondering predictive models.  The connection’s not as tenuous as you might think.  The church I’ve been going to is incredibly large…the building that is.  My best guess is it could easily hold 1000 people.  From what I’ve counted*, there seems to be about 100 people there on typical Sunday mornings, which makes the place seem quite cavernous.  This morning I was not able to do my normal count (I let a seven year old pick where to sit, and ended up in the front row), so I was only able to get a brief glance at the crowd.  It occurred to me that it’s extremely hard to estimate the size of a crowd that is in such an outsized space, especially when that crowd distributes themselves as New England churchgoers tend to.
All of this got me to browsing around the web, looking for any data on church attendance, which led me to this article for church leaders about attendance trends.  It’s a bit long, but it has some interesting research in to who goes to church and who says they go to church.  What struck me as interesting though, was point number 7, on page number 5.  If you don’t feel like clicking on the link, it’s a model of how church attendance in America will look by 2050 (percentage of population down, raw numbers up).
What struck me about this was what a funny thing this was to model.  In order to model church attendance, one must fundamentally presume that it is a purely sociological phenomena that is likely to trend consistently for 40 years.  While I think that can make for some interesting numbers on a screen, it actually seems to violate some assumptions most Christians themselves would hold (i.e. that there is a Divine force involved that might not work on a linear scale).  I’m not saying he shouldn’t have modeled this, but it did get me thinking about what types of behavior lend themselves to modeling and which ones do not.  Some phenomena change linearly, some exponentially, some decrease/increase step-wise.  I’m not sure which one church attendance fits in to, but I’d be interested in seeing the rationale for picking one over the others.
I’ve had a few people send me some studies that relied on models, and I think I’m going to try to take a look at some of them this week.  This could get interesting.
*I count people during hymn singing time.  I probably started doing this when I was about 4, as far as I can recall. 

Friday Fun Links 3-29-13

Oh man, here’s one that’s appropriate…a gif of winter disappearing!!!

This one’s personal, because this is my field.  Even if this doesn’t quite live up to expectations, every weapon in the arsenal gives all of us a better shot.

This is possibly the most interesting theory I’ve seen on why women don’t stay in STEM.  In case you’re curious, using SAT scores as a measure, my math and verbal skills are identical to within one point.

This is my pick for gif of the week.

Now here’s my favorite dinosaur site this week.  It might even teach mr how to say archaeopteryx correctly!