The series premiere of United Stats of America (See what they did there?) on History is tonight at 10/9c.

Episodes explore the stats that help us understand how much money we make (and what we spend it on), how long we will live (and how we will die), what we do with our free time (and how to make more of it) and a whole lot more. In one episode, the Sklars explain how the deadliest animal in America is neither the snake nor the shark but rather the deer. In another, viewers learn that Americans waste 4.2 billion hours a year stuck in traffic and that, in a nation with over 3.5 million square miles of territory, 99 percent of us are crowded into only 8 percent of the land.

I watched a couple of clips and got bored quickly as they went through a bunch of numbers. It seems like a rehash of Yahoo and Huffington Post lists with jokes. I’m setting my expectations low, but maybe there’ll be more to it in the full episodes.

[Thanks, Gary]

Researchers at the School of Computer Science at Carnegie Mellon University investigate the structure of cities in Livehoods, using foursquare check-ins.

The hypothesis underlying our work is that the character of an urban area is defined not just by the the types of places found there, but also by the people who make the area part of their daily routine. To explore this hypothesis, given data from over 18 million foursquare check-ins, we introduce a model that groups nearby venues into areas based on patterns in the set of people who check-in to them. By examining patterns in these check-ins, we can learn about the different areas that comprise the city, allowing us to study the social dynamics, structure, and character of cities on a large scale.

It’s most interesting when you click on location dots. A Livehood is highlighted and a panel on the top right tells you what the neighborhood is like, related neighborhoods, and provides stats like hourly and daily pulse and a breakdown location categories (for example, food and nightlife). Does foursquare have anything like this tied into their system? They should if they don’t.

There’s only maps for San Francisco, New York City, and Pittsburgh right now, but I’m sure there are more to come.

Want more on the clustering behind the maps? Here’s the paper [pdf].

We’ve seen life expectancy at the country and state levels, but the Institute for Health Metrics and Evaluation, a health research center at the University of Washington, recently released life expectancy data at the county level. The press release focuses on the lower life expectancy of girls born in 2009 compared to those born ten years before. However, the main takeaway from the IHME map, while interactive, is that life expectancy has improved. I wanted to see where life expectancy dropped during the decade.

Update: Brett and Jørgen in the comments make good points on caveats of small-county life expectancy. Is this just statistical noise?

Welcome to Anthropocene:

Scientific concepts like the Anthropocene, planetary boundaries and planetary stewardship have heralded a profound shift in perception of our place in the world: a growing evidence base of scientific observations show we have become the prime driver of global environmental change. These new concepts are powerful communication tools as we move towards global sustainability.

There’s also a non-narrated version, but I like the narration. It helps you better appreciate what you’re seeing. Oh yeah, and ooohh, purdy.

[via infosthetics]

I’ve never played Minecraft, but maybe this map showing live server connections means something to those who do. “A dot is a server or a client. Lines are traced from clients connecting to servers. Lone dots are local servers.” They also have raw hardware data available for download. [Thanks, Erik]

With the Titanic anniversary this year, Chiqui Esteban dug up graphics back from the time of the event. This one showing the time to cross the Atlantic is the best. “If only we could fly the Atlantic!”

With The Avengers coming out today in the US, artist Jer Thorp had a look at character appearances, of which there have been 127 since 1963.

We can see a big cluster of major Avengers appearing in the first few episodes, with some other big names coming in the next few years (Vision, the Avenger with the 3rd most appearances in issues, doesn’t come along until #57). While there are a couple of major additions along the way (She-Hulk & Photon in 1982), we can see that the cast of characters for the team is defined pretty early.

See Thorp’s post for additional categorizations such as gender balance and robot characters. Best enjoyed in high resolution.

I’ve been reading papers on how people learn statistics (and thoughts on teaching the subject) and came across the frequently-cited work of mathematical psychologists Amos Tversky and Daniel Kahneman. In 1972, they studied statistical misconceptions. It doesn’t seem much has changed. Joan Garfield (1995) summarizes in How to Learn Statistics [pdf].
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A while back, Robert Kosara and Caroline Ziemkiewicz shared their work on Parallel Sets, a way to visually explore categorical data. Software developer, Jason Davies, just ported the technique to Data-Driven Documents (D3). The interactions for sorting and rearranging are similar to the Kosara and Ziemkiewicz version, but the D3 version of course runs in the browser and has some nifty transitions. Try toggling the show curves box and the icicle plot one.