The importance of context

The New York Times ran an article in today's paper describing the differences in methodology used to develop suicide rates for the military, and the methodology used to develop the rate for the civilian population. The Times says that Pentagon medical statisticians use

a total population figure that includes all Guard members or reservists who spent any period of time on active duty in a given year, even if it was only a few days. According to that approach, the total active military population was about 1.67 million for all of 2009, a review of Pentagon data shows.

But at almost any given moment, the United States military is much smaller than that. Another office of the Pentagon, the Defense Manpower Data Center, the personnel record-keeping office, used a total population number of about 1.42 million service members in 2009. That figure was calculated by including only National Guard and reserve troops who had been on active duty for at least six months in a given year.

Therefore, because the denominator is too large, the military has been understating the suicide rate. (You can find a reasonably explanation of calculation of a rate here.) Why is this important? Because when the military rate and the civilian rates are comparable, there's less of a problem.

Statistics in context

These might seem like unrelated subjects, but they're not entirely - both are about how to apply statistical analysis in a context that might not seem like a reasonable candidate. The first, "The Evolution of King James" by Kirk Goldsberry, is about LeBron James and his improvement in scoring:

Over the years, James has attempted thousands of field goals, but those shots are going in at much higher rates recently. In James's rookie year he shot 42 percent from the field and 29 percent from beyond the arc. This year those numbers are 56 percent and 39 percent, respectively. There are two reasons for that substantial improvement in his field goal percentage: (1) He's a much better shooter now, and (2) also a larger share of his shots are close to the basket now.

How did he make the change? And almost more important, how did he know that he wanted to make a change and what change to make? James listened to some commentary. He thought hard about his game. And he changed it, going from a 3-point and wing shooter to a post shooter. Here are his most common shot locations, during James's first and second years in Miami:

The story is about hard work - grueling work - and about using numbers, and context, to guide that work.

The other story, "Solving Equation of a Hit Film Script, With Data," by Brooks Barnes in today's New York Times has generated a large number of comments and shot almost to the top of the most emailed list. when I read the article this morning I was initially in the camp of "you can't measure art" until I got to these paragraphs:

Mr. Bruzzese emphasized that his script analysis is not done by machines. His reports rely on statistics and survey results, but before evaluating a script he meets with the writer or writers to “hear and understand the creative vision, so our analysis can be contextualized,” he said.

But he is also unapologetic about his focus on financial outcomes. “I understand that writing is an art, and I deeply respect that,” he said. “But the earlier you get in with testing and research, the more successful movies you will make.”

The service actually gives writers more control over their work, said Mark Gill, president of Millennium Films and a client. In traditional testing, the kind done when a film is almost complete, the writer is typically no longer involved. With script testing, the writer can still control changes.

One Oscar-winning writer who, at the insistence of a producer, had a script analyzed by Mr. Bruzzese said his initial worries proved unfounded.

“It was a complete shock, the best notes on a draft that I have ever received,” said the writer, who spoke on the condition of anonymity, citing his reputation.

It's partly the comment about context. But it's also partly, I think, the acknowledgment that Bruzzese is doing some interpreting too. What do you think?

That's a map of state-by-state obesity trends in the US, measured by BMI (body mass index). That's a pretty rapid shift, in the 25 years from 1986 to 2010. Further data from the CDC here. I've written about obesity before, here for example, but it's always good to see the data in a larger context.

Context: it's how you use the numbers, not what they are

The normally extremely clear writer James Fallows (his terrific blog on politics, technology, and beer, among other things, is here) has posted a letter from one of his readers. The full blog post is here; the excerpt I'm interested in is:

First, our public policy discussion has become too wonkish, by being entirely focused on measurable outcomes at the expense of all others.  (Another example: the health care debate, the vast majority of which was about costs instead of the moral imperative of universal health care)...

It may just be the writing (to repeat, it's not Fallows' but a reader's comment), but this strikes me as an example of someone blaming the numbers, as opposed to the interpretation of the numbers, for the politics. Sometimes a mathematical model is our best chance of understanding what is happening in the world (even if that understanding is weak). But it's our interpretation of the numbers - the context we give it - that guides how we use them. Numbers are never just numbers.