Nate Silver says the weatherman is not a moron.

Still, most people take their forecasts for granted. Like a baseball umpire, a weather forecaster rarely gets credit for getting the call right. Last summer, meteorologists at the National Hurricane Center were tipped off to something serious when nearly all their computer models indicated that a fierce storm was going to be climbing the Northeast Corridor. The eerily similar results between models helped the center amplify its warning for Hurricane Irene well before it touched down on the Atlantic shore, prompting thousands to evacuate their homes. To many, particularly in New York, Irene was viewed as a media-manufactured nonevent, but that was largely because the Hurricane Center nailed its forecast. Six years earlier, the National Weather Service also made a nearly perfect forecast of Hurricane Katrina, anticipating its exact landfall almost 60 hours in advance. If public officials hadn’t bungled the evacuation of New Orleans, the death toll might have been remarkably low.

I like the bit later in the article that describes the number crunching machine and how humans are involved in the analysis. The National Weather Service has heavy-duty computing power to process data coming from weather stations across the country, but the computer is still bad at doing a lot of things.

To most people, statistics means plugging numbers into an advanced calculator that spits out values, without much thought involved. Those people don’t work with data.

The elections season is in full swing, and the New York Times graphics department ramps up its election coverage. With newly hired Mike Bostock teamed up with the Times’ interaction guy, Shan Carter, I’m sure we’re in for some interesting work.

The two, along with Matthew Ericson, covered the words used at the Republican and Democratic Conventions, but yesterday they put up an interactive that shows the words used at both conventions.

Each bubble represents a word, and the bigger the bubble the more often it was used. The blue and red split compares word usage of Democrats and Republicans, respectively, and bubbles are arranged horizontally left to right, from words favored by Democrats to those favored by Republicans. For example, “forward” is far to the left, and “fail” is far to the right.

While the visual provides a sense of what was talked about, the best part is that the visualization is an interface into the transcripts. When you click on a word, quotes that use that word are shown, so you can see what was actually said alongside keywords. Plus, you can enter your own word or phrase, and a new bubble is placed accordingly with the corresponding text on the bottom.

The 8-inch cube RGB Colorspace Atlas by artist Tauba Auerbach shows every color in said colorspace. Cubic rainbow. What does it mean? [Colossal via @periscopic]

Remember photographer Noah Kalina? He took a picture of himself every day for six years and made a time-lapse video with the photos. The Simpsons even did a spoof that showed Homer’s life over a couple of minutes. Kalina’s kept the picture-taking going, and it’s been twelve and a half years now. He made a new video.

Six years is a long time, but you didn’t see that much change in the first video. In this one, you can start to see the age in his eyes. The forty-year update will be something to see.

[via kottke]

Nancy Lublin, CEO of Do Something, gives a five-minute TED talk on the potential in analyzing text messages. During a texting campaign, Do Something started to receive texts from troubled teenagers, that ranged from bullying to rape, which led to the organization’s work in setting up a texting hotline. Lublin hopes that, once the system is built, the data gathered from these messages can be used as a census of problems, and can perhaps be used in the same way that Target uses data to figure out if women are pregnant — but to save lives, instead of figuring out what coupons to send.

[Thanks, Tommy]

After identifying 129 metropolitan regions that represent 35 percent of the world’s urban population, LSE Cities mapped some of the densest areas with a simple black and white color scheme. The patterns reveal a footprint of where the much of the world’s population lives.

To get a sense of the spatial dynamics of these city regions, we mapped 12 cases at the same scale with core built-up areas in black and peripheral areas in grey. By comparing the footprint of the world’s largest urban conurbation in Tokyo with Atlanta, our sample’s most land-hungry city region, we see that roughly the same amount of land is occupied by 42 million as by 7.5 million people. Meanwhile, the map of London shows that 14 million people are spread across South-east England.

In other words, that’s a whole lot of people packed into Tokyo. I wonder what these maps would look like with Tokyo density.

Feeding off the momentum from Stephen Wolfram’s personal analytics earlier this year, Wolfram|Alpha launched Facebook Analytics, which spits out graphs about your profile and your friends. You can see your activity over time, weekly distributions, and some general information about how people like and comment your status updates.

I’ve only updated my Facebook status a few times this year, so the profile-focused information is interesting to me, but the second half of the report provides high-level aggregates about your friends. For example, I’m apparently at a stage in life where most of my friends are either married or in a relationship. You can also see how your friends are connected via a network graph.

So you get more detail than you do out of current infographic-generators. The hook though is the links within the report that lead to information about your birthday or where you were born, kind of like when you end up reading about sasquatch on Wikipedia when your original search was actually work-related.