Matt Yglesias

Industrial Capacity and Utilization

Here’s a chart that nicely illustrates our predicament:

Via.

Breaking Down the Divisions

Here’s a useful table to contemplate now that we’re in NFL playoff season:

Apparently the two West divisions were the worst, and second-worst performances since the AFL-NFL merger. He then offers us some questionable statistical analysis under the guise of elucidated “conspicuous trends” from the history of this data:

The most compelling of these is that 26 of the 37 Super Bowl winners since the merger came from divisions that placed in the top three in win percentage during that season. This trend gets even stronger if the start year is moved to 1977, as 25 of the 30 world champions in that time hailed from one of the top three divisions based on win percentage. This trend stretched beyond Super Bowl champs, as 42 of the 72 conference champions since the merger came from the top three divisions. (These numbers don’t include the 1982 season because divisional play was not used that year.)

The historical evidence also shows strong indications for playoff teams that come from the bottom divisions. There were six divisions from 1970 through 2001, and only one time during that era did a team that came from the division with the worst win percentage win a Super Bowl (1999 St. Louis Rams). In fact, playoff teams from the sixth division during those years won only 24 playoff games, and seven of those were wild-card victories.

Another way of looking at this is that good teams tend to win the Super Bowl, good teams tend to have very good regular season records, and since NFL divisions are small having a very good team in your division tends to pull your division’s overall record upward.

America in Black and White

Tom Lee says that the “purple America” images I linked to the other day are actually misleading in their own way for a few reasons:

But also true: visualizing information by using a linear red/blue scale is about the worst way possible to make data legible to the human eye. First: our vision is logarithmic. When a photographer drags out his “50% gray” card for measuring lighting, it’s actually 18% gray. Judging by the triangular key in the corner of Vanderbei’s image, he’s just taking the percentage of vote totals and translating it flatly to 8 bit color — a 100% Republican district gets an RGB 24-bit value of (255,0,0).

The colors themselves are also a problem. As I’m sure you all remember keenly from this post I wrote in 2006, perceptual image codecs spend more bits on brightness than on color because the color-sensing cones in your eyes have a much lousier dynamic range than the light-sensing rods. We’re worse at distinguishing between levels of color than between levels of brightness. And since the percentage of the vote in any given spot on the map should always sum to 100, with negligible green (third party) contributions, the brightness will be relatively uniform (although admittedly not quite due to the perceptual differences between colors — monitor calibration and colorspace begins to enter the picture here, and is just as hideously complex as you might imagine).

He suggests instead a simple grayscale:

That shows the same rough similarity between the two elections, but highlights the geographical variation in a clearer way and lets you see where things did change: “Things are more black and white than they may seem, and certainly less purple.”

Where The Singles Are

You may recall this chart, showing which cities have a surplus of single men and which have a surplus of single women, making the rounds on the tubes a while back:

An interesting result. But now via Ezra Klein, a more interesting result — an interactive map of the same data that lets you examine particular age brackets. What it shows is that the age-linked variation is much larger than the geographical variation. Women tend to marry earlier than men, so in younger cohorts men outnumber women everywhere. Here’s the 20-34 bracket:

Single men outnumber single women everywhere in the young bracket. Fun fact: “The switchover from extra men to extra women starts at 35-39 for most big East Coast cities, but doesn’t hit New York until 40-44.” Of course in practice dating is rather socioeconomically bounded, and the number of number of single male high school dropouts in a given metro area has relatively little to do with a college educated professional woman’s dating prospects (though my dad didn’t finish high school and my mom went to Cornell so I’m well aware that there are exceptions), so even this more sophisticated model still leaves some real gaps in one’s understanding.