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"Tell the chef, the beer is on me."
By way of Chris Volinsky, a quiz dilemma for students who want extra credit. It's a variation on the Prisoner's Dilemma, a popular game theory example that uses two criminals instead of students and lesser jail time instead of extra credit.
What's your answer? I take the two.
Claire Cain Miller for the Upshot on when algorithms discriminate:
There is a widespread belief that software and algorithms that rely on data are objective. But software is not free of human influence. Algorithms are written and maintained by people, and machine learning algorithms adjust what they do based on people’s behavior. As a result, say researchers in computer science, ethics and law, algorithms can reinforce human prejudices.
I bring this up often, because I apparently still hold a grudge, but I will always remember the time I told someone I study statistics. He responded skeptically, "Don't computers do that for you?"
In the words of Jeffrey Heer: "It's an absolute myth that you can send an algorithm over raw data and have insights pop up."
Kind of fun. Branden Rishel mapped just the time zones. No borders or countries for context. In case you're confused and want to know where these lines come from, BBC News made an interactive that explains why time zones are the way they are.
Tags: time zones
Map posters are easy to come by for major cities. But if you want one for a less densely populated area of the world, you might be out of luck. Mapiful can help. Select anywhere in the world, and get a streamlined black and white poster, based on OpenStreetMap data.
After you have your location, pan and zoom to get the exact area you want, and then customize the labeling and choose between four simple themes.
Posters not your thing? Maybe you want map clothing.
Using images taken by New Horizons between June 27 and July 3, this is the latest NASA map informally named the Whale and the Donut. Now, use your imagination here (because space!). The dark area on left is the whale, representing about 1,860 miles of length, and the tail in the left corner is cupping the donut.
Hopefully we'll get a better look come next week. I'm guessing they're an actual whale and donut. But I'm no scientist.
Students want to get into a school, and schools want certain students. Match. Med students want to get into a specific residency program, and certain programs want specific students. Match.
Tim Harford explains the role of matching algorithms to make picking fair for all parties. The process gets messy when you start looking at thousands of individuals and organizations with multiple preferences each.
The deferred acceptance algorithm is just the start of a successful market design, because details matter. In New York City, there are different application procedures for certain specialised schools. When assigning hospital residencies, the US National Resident Matching Program needed to cope with pairs of romantically attached doctors who wanted two job offers in the same city. These complexities sometimes mean there is no perfect matching algorithm, and the challenge is to find a system that is good enough to work.
The New Horizons spacecraft launched on January 19, 2006 and is set to fly by Pluto next week on July 14, 2015. The New York Times provides a short documentary on the journey and the hope for what the flyby provides.
It's a combination of researcher interviews and scientific graphics. So good, even if you don't follow space-related news. Set aside the 13 minutes and 21 seconds to watch the whole thing.
Then keep track of the event at NASA's site for the mission.
Most of us have seen the True Size of Africa graphic that squishes multiple countries into an area we normally see as much smaller. This is because of projections, which places a spherical planet in a two-dimensional space. Different projections have different tradeoffs. Even the True Size graphic has issues.
This interactive by Zan Armstrong tries a different route by overlaying two globes against each other.
I was inspired to create this after reading a friend's account of his time fighting Ebola in Sierra Leone. He was frustrated with misunderstanding about the disease, including that a "school in New Jersey that panicked and refused to admit two elementary school children from Rwanda. Never mind that Rwanda is 2,600 miles from the epidemic area in West Africa. That’s the distance from my apartment in DC to Lake Tahoe."
Rotate each globe on the left to the areas of interest. The globe on the right shows two highlighted areas in the same view.
I know next to nothing about soccer. Like there's nothing, and then I'm sitting right there next to it. But, the New York Times provides an explanation of the U.S. women's current offense-focused strategy with some simple diagrams and a video, and I feel a little more edumacated.
I like the particular frame above that shows the gaps and seams that players try to attack. Basketball uses the same terminology, so I'm familiar, but this is the first time I've seen it so concretely.
"Millions of data scientists and academic researchers use R language every day and want to collaborate with their peers to share visualization and analysis techniques," said Jim Zemlin, executive director at The Linux Foundation. "The R Consortium will promote the sharing of ideas and accelerate findings that make R even better for business, research and academic purposes."
Nice. I can feel the momentum. [via Simply Statistics]
Maps are fun to look at and get easier to make every day, so there's a lot of them floating around in the world. But before you sit down to enjoy that big, juicy map, take in some advice from geographer Andrew Wiseman to avoid looking the fool. A fool? A fool, I say.
It's no surprise then that people often assume maps are accurate, because it's so often unclear how they are made—maps are "arcane images afforded undue respect and credibility" that are "entrusted to a priesthood of technically competent designers and drafters," as Monmonier puts it. Almost everybody can write, but not everyone can make a map.
Tips include: Don't trust extreme titles, look for the data source, and note the color distributions. As is usually the case, we can piggyback on most of this advice for visualization in general.
And this of course doesn't mean you treat every map with extreme skepticism and strip away every possible ounce of joy. Just pay attention as you read, like you would anything, written or otherwise.
Tags: data literacy
Most people who use R on the regular learned the language in the context of a subject outside of programming. They learned R as they learned statistical methods, or they picked up bits of R as they learned about visualization. However, if you learn R purely as just a language — without the domain-specificity — or you already program in a different language, R might seem strange at times.
In this talk, John D. Cook explains some of the "quirks" in R and why, maybe, they're not so strange.
I picked up R after three semesters of computer science in college, and that little bit of background actually seemed to make learning R a lot easier for me. So maybe the key is to be a horrible programmer at first (I was and still am in some ways), and R won't seem so quirky. [via Revolutions]
Gertrude Weaver, 116 years old, was the oldest person in the world for five days before she passed. These short tenures have grown more common in recent years. David Goldenberger for FiveThirtyEight looks at the tenure of previous record holders.
Weaver's five-day run as the oldest person in the world was short, but it turns out that the oldest person in the world never holds that title for very long. Since records started being kept in the 1950s, the average tenure has been just around a year, according to the Gerontology Research Group; it has dipped to just seven months since the year 2000. Weaver's incumbency isn't the shortest in recent years; North Carolina's Emma Tillman died four days after becoming the world's oldest person in 2007.
Dang, Jeanne Calment.
Under the directive of the Federal Housing Finance Agency, started to release detailed loan-level data in 2013. Todd W. Schneider looked at the data recently, evaluating default rates — the proportion of loans that fell into deliquency — with a bit of geography.
California, Nevada, New Mexico, and Florida were in particularly bad shape during the 2005 through 2007 bubble. Some counties had more than 40 percent of loans default. I don't know much about loans, but that seems high. And there was plenty of contrast as you evaluate nearby areas.
It's less than 100 miles from San Francisco to Modesto and Stockton, and only 35 miles from Anaheim to Riverside, yet we see such dramatically different default rates between the inland regions and their relatively more affluent coastal counterparts.
Aside from the analysis though, maybe the most interesting bit is Schneider's previous experience as a mortgage analyst and the contrast of analysis a few years ago to now.
Between licensing data and paying for expensive computers to analyze it, you could have easily incurred costs north of a million dollars per year. Today, in addition to Fannie and Freddie making their data freely available, we’re in the midst of what I might call the “medium data” revolution: personal computers are so powerful that my MacBook Air is capable of analyzing the entire 215 GB of data, representing some 38 million loans, 1.6 billion observations, and over $7.1 trillion of origination volume. Furthermore, I did everything with free, open-source software. I chose PostgreSQL and R, but there are plenty of other free options you could choose for storage and analysis.
You can check out the code on GitHub. [Thanks, Todd]
On April 1, Reddit posted a simple button with a 60-second timer that counted down to zero. Every time the button was pressed by a unique Reddit user, the timer reset to 60 seconds. Yesterday, more than two months and 1,008,316 presses later, the timer finally made it to zero seconds without a press.
It was the social experiment that just kept on going, and Reddit released the click data — a timestamp for each click. Could be fun if you're looking for a time series to play with.
Thank you to Metis for sponsoring the feed this week.
Enrollments opened today for Data Visualization with D3.js.
You may attend a live stream presentation on Wednesday, June 10 at 7pm EDT to see a Data Visualization with D3.js presentation by Kevin Quealy, Metis Instructor and Graphics Editor for The New York Times.
RSVP here to attend our event live stream and chat.
Kevin Quealy is Graphics Editor at The New York Times and a contributor to The Upshot, the Times' data-centric vertical about policy, politics and everyday life. He has taught journalism and data visualization courses at N.Y.U., the University of California, Berkeley and the City University of New York.
Before coming to The New York Times, Kevin served as a Peace Corps volunteer in South Africa. He has a Master's degree from the Missouri School of Journalism and a B.A. in physics from Gustavus Adolphus College in St. Peter, Minnesota.
The Washington Post has a straightforward calculator to figure out how much it will cost you to cut out cable television and replace it with streaming services. Just select the features you want, and the cost on the right tells you how much. Kind of fun to click at.
There's a table at the end that shows what each device, such as the Apple TV or Roku have. I wish that got highlighted in some way, depending on what services you want. It's just a static table as it is now.
I've given a good amount of thought to quitting cable myself but never did it. I keep cable for the live sports, mainly for basketball. The NBA streaming service is fine, but a lot of the good games are blacked out, and I tried a plain old TV antenna but the reception is horrible. I couldn't get any of the major networks. And so, after all the back-of-the-napkin math, I always end up back at the beginning — keeping my cable subscription and hating Comcast.
"Tell the chef, the beer is on me."
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