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"Tell the chef, the beer is on me."
A while back beckmw found the average length of a dissertation for various fields of study, based on digital archives at the University of Minnesota. Here's a follow-up to that data scrape with average lengths of masters' theses, again for various fields. Medical Chemistry wins this round.
By the way, the colors don't mean anything. They're just there for flourish.
On the upside, the R code for scraping along with the resulting data is available for download.
"If it seems as if the list of presidential candidates for 2016 is growing by the day, that is because it is, at least on the Republican side." Alicia Parlapiano for the New York Times charts the changing campaign calendar with more candidates and earlier starts. Because you know, we're not even halfway through 2015 yet.
On the upside: more charts.
Kevin Ferguson examined color usage in Western films from various angles. One of those was the sum image using the movie frames every ten seconds.
These shapes and colors are evocative in a way that tea leaves and tarot are: they don't actually tell you much about what you're looking at, but they allow you an emotional response confirmed or denied once you come to discover what the image "really" is.
The methods themselves you've seen before, but probably not used in this way.
Iowa released liquor sales data for weekly purchases at the store level.
This dataset contains the spirits purchase information of Iowa Class "E" liquor licensees by product and date of purchase from January 1, 2014 to current. The dataset can be used to analyze total spirits sales in Iowa of individual products at the store level.
There are over three million rows that contain a store name, address, liquor category, liquor vendor, and cost. I imagine this could be a fun spatial time series dataset to play with. Look for seasonal trends, when stores expect to sell more rum or vodka, brand bestsellers, or regional favorites. Even though it's just for Iowa, there's probably a close relationship to national sales.
See some preliminary documentation by Dan Nguyen on how to get started.
In Pieces by designer Bryan James is an animated piece that uses simple geometric shapes to depict thirty endangered species.
Each species has a common struggle and is represented by one of 30 pieces which come together to form one another. The collection is a celebration of genic diversity and an attempting reminder of the beauty we are on the verge of losing as every moment passes. These 30 animals have been chosen for their differences, so that we can learn about species we didn't know about previously as well as the struggles they have surviving. Many of them evolved in a particular way which makes them evolutionarily distinct.
And this was all done with CSS. Whoa. Find out more about the process here.
In an exploration of the connection between humans an nature, artist Ren Ri uses beeswax as his medium and the bee colony as the builder. Yeah.
Because a colony will follow the queen bee and build a hive based on the pheromones that she releases, Ri is able to move the queen such that the others in the colony act accordingly.
The three-part series is called Yuansu, which translates to "a comprehension of the gestalt of life". One part is a collection of abstract sculptures, and another is a performance with the bees themselves. But the first part, which Ri and the bees created back in 2008, is a series of geographic maps.
Here's the United States:
The Korea peninsula:
The Citizen Ex browser extension guesses where you're geographically located on the web. That is, it guesses where the server — the one you just pulled that website from — is in the world. It also guesses where you are physically located. The extension keeps track of these locations and computers something called Algorithmic Citizenship.
Algorithmic Citizenship is a form of citizenship which is not assigned at birth, or through complex legal documents, but through data. Like other computerised processes, it can happen at the speed of light, and it can happen over and over again, constantly revising and recalculating. It can split a single citizenship into an infinite number of sub-citizenships, and count and weight them over time to produce combinations of affiliations to different states.
In 1971, the Las Vegas metro area was home to 262,000 people. Today, the population is approaching 2 million. Since 1990, its footprint has more than doubled. Managing urban growth is critical to the future of the West's previous — and declining — water supplies.
The interaction is slick. Drag the cursor back and forth in the timeline on the bottom to quickly scroll through time. The green shading shows the quickly increasing Las Vegas city limits. The illustrated skyline changes too, which is a nice touch that places the data in a more relatable context.
They probably could have stopped there, and the piece would've been good, but you can also change the map perspective with a click and drag.
The US government doesn't keep a complete record of fatal shootings by police, but with recent events, it's become increasingly obvious why such data is important. So instead of waiting, the Guardian built their own database.
The database will combine Guardian reporting with verified crowdsourced information to build a more comprehensive record of such fatalities. The Counted is the most thorough public accounting for deadly use of force in the US, but it will operate as an imperfect work in progress — and will be updated by Guardian reporters and interactive journalists as frequently and as promptly as possible.
In May 2015 alone, the data counts 80 people.
Search and filter to areas of interest. Or, download the data.
Million Base is a database of 2.2 million chess games. Steve Tung visualized chess piece journeys based on this data, for each piece on the board. Above is the footprint for the white knight. Each thin line represents 500 moves, and from what looks like a little bit of random noise to offset each line, you see a more prominent path for more frequent hops.
Of course, because of starting points and game rules, there's a unique pattern for each piece.
Here's the black queen, which relatively more board coverage than others:
The white king, which is more limited in movement:
In contrast, here's the black pawn that starts in position b7.
After seeing an isochrone map drawn by Francis Galton, Peter Kerpedjiev was curious if he could apply the method to travel times in Europe.
It conjured images of steam trains (were the trains in 1900 still running on steam?) chugging along between the imperial centers of Vienna and Budapest. It made me wonder about how people commuted from the train station to their final destination. It made me question my conception of how long it took to get from place to place. Most of all, however, it made me wonder what such a map would look like today.
Using data from the Swiss public transport API, Kerpedjiev built similar maps with major cities as starting points. Simply select a city, and the map shows how long it would take to get to areas in Europe.
I fully expect someone to do something similar for the US within a month. [via Guardian]
You're headed to the subway platform and you hear a train coming. The warm musty air that blows directly into your nostrils is near. So you speed up your steps. Oh forget it, who are you trying to impress? You run to make sure you get to the platform. Yes, you made it! You hop on with your heart rate up a few beats. Nice.
But the doors stay open.
The train isn't moving.
What gives? ARGH.
Of course, there's a perfectly logical explanation. The Metropolitan Transportation Authority provides a scenario in 8-bit format.
As we've seen, it doesn't take much to throw off the schedule of a transportation system. Sometimes the weird delay you experience is just the system trying to make things better overall. [Thanks, @reconbot]
I tried playing Minecraft a couple of times but quickly lost interest. Clearly not the case for millions of others. Wired did a bunch of back-of-the-napkin math on how big Minecraft is and put it in an 8-bit video. Find answers to such burning questions such as the volume of the Minecraft world or the time it would take to explore the entire world in real life.
My niece and nephew play the game and its incarnations all the time. I think they even make YouTube videos of them playing. I still don't get it.
Last week, graduate student Michael J. LaCour was in the news for allegedly making up data. The results were published in Science. LaCour's co-author Donald Green requested a retraction, but the paper stayed while the request was considered. Today, Science formally fulfilled the request.
The reasons for retracting the paper are as follows: (i) Survey incentives were misrepresented. To encourage participation in the survey, respondents were claimed to have been given cash payments to enroll, to refer family and friends, and to complete multiple surveys. In correspondence received from Michael J. LaCour's attorney, he confirmed that no such payments were made. (ii) The statement on sponsorship was false. In the Report, LaCour acknowledged funding from the Williams Institute, the Ford Foundation, and the Evelyn and Walter Haas Jr. Fund. Per correspondence from LaCour's attorney, this statement was not true.
This is like a car accident I can't look away from, and it continues to get worse. Virginia Hughes for BuzzFeed reported a discrepancy in LaCour's listed funding sources, as noted in the Science retraction.
In the study's acknowledgements, LaCour states that he received funding from three organizations — the Ford Foundation, Williams Institute at UCLA, and the Evelyn and Walter Haas, Jr., Fund. But when contacted by BuzzFeed News, all three funders denied having any involvement with LaCour and his work.
Then Jesse Singal for Science of Us looked closer at LaCour's CV and it appears he made up his largest funding source.
The largest of these is a $160,000 grant in 2014 from the Jay and Rose Phillips Family Foundation of Minnesota. But Patrick J. Troska, executive director of the foundation, which is focused on projects that combat discrimination, wrote in an email to Science of Us, "The Foundation did not provide a grant of any size to Mr. LaCour for this research. We did not make a grant of $160,000 to him."
Just yesterday, Singal reported another discrepancy in LaCour's CV: A made up teaching award. When Singal asked LaCour about it, LaCour removed it from the CV, posted a new file to his site, and said he didn't know what Singal was talking about. The original CV was still cached on the UCLA server. Oof.
People have also started to examine LaCour's previous work, and it's not looking good.
Since this whole thing started, LaCour has stayed mostly quiet on the advice of his lawyer and says he will have a "definitive response" on or before May 29, 2015. That's tomorrow. And so I wait, unable to look away.
As a former graduate student, I keep trying to put myself in a similar situation. It's crazy. I want LaCour to drop down a response — a giant stack of papers, pages and pages long — raise his hands in the air, and just disprove everything. But it doesn't look like that's going to happen.
Those who grow up in poorer families are less likely to go to college, and those who grow up in richer families are more likely. The question is: How much does the likelihood of college attendance increase as family income increases? Gregor Aisch, Amanda Cox, and Kevin Quealy for the Upshot ask you this question. Draw a curve on a blank chart, and then compare your guess to reality and other readers' guesses.
This is great.
From a technical point of view, the interaction is straightforward for readers, and with simple cues as you draw, it's clear how to complete the task. Nice.
More interesting to me though is the challenge to readers to think about the relationship between income and college attendance. That seems like a pretty advanced task for a wide audience. (Although I'm guessing Upshot readers are more accustomed to reading and using x-y plots that the average person. Update: Then again, it's currently on the nytimes.com front page, so there's that.) So there's some teaching along the way, namely a handful of curve examples within the text.
But the key is the comparison after you draw a curve. You get short bullet points about how you did relative to other readers, and of course, a comparison against reality.
Well, here, just try it yourself.
"Tell the chef, the beer is on me."
"Basically the price of a night on the town!"
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