andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-396 knowledge-graph by maker-knowledge-mining

396 andrew gelman stats-2010-11-05-Journalism in the age of data


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Introduction: Journalism in the age of data is a video report including interviews with many visualization people. It’s also a great example of how citations, and further information appear alongside with the video – showing us the future of video content online.


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2 It’s also a great example of how citations, and further information appear alongside with the video – showing us the future of video content online. [sent-2, score-2.732]


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Introduction: Journalism in the age of data is a video report including interviews with many visualization people. It’s also a great example of how citations, and further information appear alongside with the video – showing us the future of video content online.

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Introduction: This video caught my interest – news video clip (from this post2 ) http://www.stat.columbia.edu/~cook/movabletype/archives/2011/02/on_summarizing.html The news commentator did seem to be trying to point out what a couple of states had to say about the claimed relationship – almost on their own. Some methods have been worked out for zombies to do just this! So I grabbed the data as close as I quickly could, modified the code slightly and here’s the zombie veiw of it. PoliticInt.pdf North Carolina is the bolded red curve, Idaho the bolded green curve. Missisipi and New York are the bolded blue. As ugly as it is this is the Bayasian marginal picture – exactly (given MCMC errror). K? p.s. you will get a very confusing picture if you forget to centre the x (i.e. see chapter 4 of Gelman and Hill book)

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Introduction: This (by Frans Hofmeester) is excellent. What really makes it work, I think, is that it goes slowly enough. 2 minutes and 45 seconds is enough time for me, as a viewer, to feel like I’m living through each stage of development. If the video were sped up to go from 0 to 12 in only 30 seconds, that would be cool in its own way but would give up the sense of local stability that is characteristic of development.

4 0.16505429 1698 andrew gelman stats-2013-01-30-The spam just gets weirder and weirder

Introduction: In the inbox today, under the header, “Hidden Costs behind Milk & Dairy Consumption (video)”: Hey Professor Gelman, Our site’s production team recently released a short video uncovering the local and global impact that milk has on our lives. After spending some time on your posts, I noticed you talked about dairy products and milk so I thought I’d email you. Are you the correct person to contact in regards to the content on the site? If so, let me know if you’re interested in checking out the video. Thanks, Emily S. Hmmm . . . I guess I do talk a lot about dairy products and milk on this site!

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Introduction: Journalism in the age of data is a video report including interviews with many visualization people. It’s also a great example of how citations, and further information appear alongside with the video – showing us the future of video content online.

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Introduction: Stephanie Evergreen writes: Media, web design, and marketing have all created an environment where stakeholders – clients, program participants, funders – all expect high quality graphics and reporting that effectively conveys the valuable insights from evaluation work. Some in statistics and mathematics have used data visualization strategies to support more useful reporting of complex ideas. Global growing interest in improving communications has begun to take root in the evaluation field as well. But as anyone who has sat through a day’s worth of a conference or had to endure a dissertation-worthy evaluation report knows, evaluators still have a long way to go. To support the development of researchers and evaluators, some members of the American Evaluation Association are proposing a new TIG (Topical Interest Group) on Data Visualization and Reporting. If you are a member of AEA (or want to be) and you are interested in joining this TIG, contact Stephanie Evergreen.

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Introduction: See, for example, this report by Deborah Carr on changing attitudes about marital infidelity: Two great things about the General Social Survey are: (1) the data are freely available online , and (2) the same questions have been asked since 1972 so you get a nice long series.

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Introduction: There is a lot of data on the web, meant to be looked at by people, but how do you turn it into a spreadsheet people could actually analyze statistically? The technique to turn web pages intended for people into structured data sets intended for computers is called “screen scraping.” It has just been made easier with a wiki/community http://scraperwiki.com/ . They provide libraries to extract information from PDF, Excel files, to automatically fill in forms and similar. Moreover, the community aspect of it should allow researchers doing similar things to get connected. It’s very good. Here’s an example of scraping road accident data or port of London ship arrivals . You can already find collections of structured data online, examples are Infochimps (“find the world’s data”), and Freebase (“An entity graph of people, places and things, built by a community that loves open data.”). There’s also a repository system for data, TheData (“An open-source application for pub

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Introduction: Robert Gonzalez reports on some beautiful graphs from John Nelson. Here’s Nelson:   The sexes start out homogenous, go super segregated in the teen years, segregate for business in the twenty-somethings, and re-couple for co-habitation years.  Then the lights fade into faint pockets of pink.   I [Nelson] am using simple tract-level population/gender counts from the US Census Bureau. Because their tract boundaries extend into the water and vacant area, I used NYC’s Bytes of the Big Apple zoning shapes to clip the census tracts to residentially zoned areas -giving me a more realistic (and more recognizable) definition of populated areas. The census breaks out their population counts by gender for five-year age spans ranging from teeny tiny infants through esteemed 85+ year-olds. And here’s Gonzalez: Between ages 0 and 14, the entire map is more or less an evenly mixed purple landscape; newborns, children and adolescents, after all, can’t really choose where the

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Introduction: 10. Out of a random sample of 100 Americans, zero report having ever held political office. From this information, give a 95% confidence interval for the proportion of Americans who have ever held political office. Solution to question 9 From yesterday : 9. Out of a population of 100 medical records, 40 are randomly sampled and then audited. 10 out of the 40 audits reveal fraud. From this information, give an estimate, standard error, and 95% confidence interval for the proportion of audits in the population with fraud. Solution: estimate is p.hat=10/40=0.25. Se is sqrt(1-f)*sqrt(p.hat*(1-.hat)/n)=sqrt(1-0.4)*sqrt(0.25*0.75/40)=0.053. 95% interval is [0.25 +/- 2*0.053] = [0.14,0.36].

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Introduction: OK, here’s something that is completely baffling me. I read this article by John Colapinto on the neuroscientist V. S. Ramachandran, who’s famous for his innovative treatment for “phantom limb” pain: His first subject was a young man who a decade earlier had crashed his motorcycle and torn from his spinal column the nerves supplying the left arm. After keeping the useless arm in a sling for a year, the man had the arm amputated above the elbow. Ever since, he had felt unremitting cramping in the phantom limb, as though it were immobilized in an awkward position. . . . Ramachandram positioned a twenty-inch-by-twenty-inch drugstore mirror . . . and told him to place his intact right arm on one side of the mirror and his stump on the other. He told the man to arrange the mirror so that the reflection created the illusion that his intact arm was the continuation of the amputated one. The Ramachandran asked the man to move his right and left arms . . . “Oh, my God!” the man began

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