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    <description>recent bookmarks from kellyramsey</description>
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      <rdf:Seq>	<rdf:li rdf:resource="https://paulstepahin.wordpress.com/2013/01/06/shuffling/"/>
	<rdf:li rdf:resource="http://www.newyorker.com/tech/elements/how-to-call-bullshit-on-big-data-a-practical-guide"/>
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	<rdf:li rdf:resource="http://www.refsmmat.com/statistics/"/>
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	<rdf:li rdf:resource="http://www.survey-design.com.au/Usergraphs.html"/>
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	<rdf:li rdf:resource="http://www.comstockfilms.com/blog/tony/2009/02/25/harvards-benjamin-edelman-latest-to-be-suckered-by-avns-12byear-figure/"/>
	<rdf:li rdf:resource="http://www.theatlantic.com/culture/archive/2011/02/is-that-a-boiled-frog-in-your-pocket-or-are-you-just-happy-to-see-me/70638/"/>
	<rdf:li rdf:resource="http://bactra.org/weblog/727.html"/>
	<rdf:li rdf:resource="http://theatlantic.com/international/archive/2011/02/crowdsourcing-china-labor-strikes/70883/"/>
	<rdf:li rdf:resource="http://blog.apps.chicagotribune.com/2011/01/28/steal-this-code-the-newsapps-boundary-service-api/"/>
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  </channel><item rdf:about="https://paulstepahin.wordpress.com/2013/01/06/shuffling/">
    <title>Shuffling (Paul Stepahin | The Thirty Birds)</title>
    <dc:date>2018-01-30T22:46:32+00:00</dc:date>
    <link>https://paulstepahin.wordpress.com/2013/01/06/shuffling/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" Shuffling is typically a means to randomize the order of a deck. Here we see that a truly perfect shuffle has no such effect, returning the deck to its original order after eight repetitions. The randomization that shuffling achieves comes not from the shuffle but from the disordered accumulation of small errors, the inherent randomness of imperfect human execution. The better you are at shuffling the worse you are shuffling. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:58b779e436fc/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.newyorker.com/tech/elements/how-to-call-bullshit-on-big-data-a-practical-guide">
    <title>How to Call B.S. on Big Data: A Practical Guide (Michelle Nijhuis, The New Yorker)</title>
    <dc:date>2017-06-04T16:32:03+00:00</dc:date>
    <link>http://www.newyorker.com/tech/elements/how-to-call-bullshit-on-big-data-a-practical-guide</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" Upon encountering a piece of information, in any form, ask, “Who is telling me this? How does he or she know it? What is he or she trying to sell me?” (Journalists have their own versions of these questions.) If you’d ask it at a car dealership, West suggested to the students, you should ask it online, too. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:source>https://apple.com/iphone/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:c1e7fd90b11f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="https://medium.com/research-things/on-surveys-5a73dda5e9a0">
    <title>On Surveys (Erika Hall | Medium)</title>
    <dc:date>2017-05-31T14:31:21+00:00</dc:date>
    <link>https://medium.com/research-things/on-surveys-5a73dda5e9a0</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" What makes a survey bad? If the data you get back isn’t actually useful input to the decision you need to make or if it doesn’t reflect reality, that is a bad survey. This could happen if respondents didn’t give true answers, or if the questions are impossible to answer truthfully, or if the questions don’t map to the information you need, or if you ask leading or confusing questions.

" Often asking a question directly is the worst way to get a true and useful answer to that question. Because humans. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:source>https://apple.com/iphone/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:03032a08051b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="https://larspsyll.wordpress.com/2017/01/05/top-10-rct-critiques/">
    <title>Top 10 RCT critiques (Lars P. Syll)</title>
    <dc:date>2017-01-09T04:33:16+00:00</dc:date>
    <link>https://larspsyll.wordpress.com/2017/01/05/top-10-rct-critiques/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:501d523ba33e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://andrewgelman.com/2016/09/21/what-has-happened-down-here-is-the-winds-have-changed/">
    <title>What has happened down here is the winds have changed (Andrew Gelman)</title>
    <dc:date>2016-11-05T01:09:24+00:00</dc:date>
    <link>http://andrewgelman.com/2016/09/21/what-has-happened-down-here-is-the-winds-have-changed/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" I bring this up not in the spirit of gotcha, but rather to emphasize what a difficult position Fiske is in. She’s seeing her professional world collapsing—not at a personal level, I assume she’ll keep her title as the Eugene Higgins Professor of Psychology and Professor of Public Affairs at Princeton University for as long as she wants—but her work and the work of her friends and colleagues is being questioned in a way that no one could’ve imagined ten years ago. It’s scary, and it’s gotta be a lot easier for her to blame some unnamed “terrorists” than to confront the gaps in her own understanding of research methods.

" To put it another way, Fiske and her friends and students followed a certain path which has given them fame, fortune, and acclaim. Question the path, and you question the legitimacy of all that came from it. And that can’t be pleasant. "]]></description>
<dc:subject>data-analysis academia</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:a0eb16f8cbf2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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<item rdf:about="https://www.statnews.com/2016/09/21/chronic-fatigue-syndrome-pace-trial/">
    <title>How bad science misled chronic fatigue syndrome patients (Julie Rehmeyer | Stat)</title>
    <dc:date>2016-09-22T13:07:43+00:00</dc:date>
    <link>https://www.statnews.com/2016/09/21/chronic-fatigue-syndrome-pace-trial/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" Before the trial of 641 patients began, the researchers had announced their standards for success — that is, what “improvement” and “recovery” meant in statistically measurable terms. To be considered recovered, participants had to meet established thresholds on self-assessments of fatigue and physical function, and they had to say they felt much better overall.

" But after the unblinded trial started, the researchers weakened all these standards, by a lot. Their revised definition of “recovery” was so loose that patients could get worse over the course of the trial on both fatigue and physical function and still be considered “recovered.” The threshold for physical function was so low that an average 80-year-old would exceed it.

" In addition, the only evidence the researchers had that patients felt better was that patients said so. They found no significant improvement on any of their objective measures, such as how many patients got back to work, how many got off welfare, or their level of fitness. "]]></description>
<dc:subject>academia data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:da782ab1badf/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:academia"/>
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</item>
<item rdf:about="http://www.nature.com/news/scientific-method-statistical-errors-1.14700?WT.mc_id=TWT_NatureNews">
    <title>Scientific method: Statistical errors (Regina Nuzzo | Nature News &amp; Comment)</title>
    <dc:date>2015-01-19T17:02:43+00:00</dc:date>
    <link>http://www.nature.com/news/scientific-method-statistical-errors-1.14700?WT.mc_id=TWT_NatureNews</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" For all the P value's apparent precision, Fisher intended it to be just one part of a fluid, non-numerical process that blended data and background knowledge to lead to scientific conclusions. But it soon got swept into a movement to make evidence-based decision-making as rigorous and objective as possible. This movement was spearheaded in the late 1920s by Fisher's bitter rivals, Polish mathematician Jerzy Neyman and UK statistician Egon Pearson, who introduced an alternative framework for data analysis that included statistical power, false positives, false negatives and many other concepts now familiar from introductory statistics classes. They pointedly left out the P value.

" But while the rivals feuded — Neyman called some of Fisher's work mathematically “worse than useless”; Fisher called Neyman's approach “childish” and “horrifying [for] intellectual freedom in the west” — other researchers lost patience and began to write statistics manuals for working scientists. And because many of the authors were non-statisticians without a thorough understanding of either approach, they created a hybrid system that crammed Fisher's easy-to-calculate P value into Neyman and Pearson's reassuringly rigorous rule-based system. This is when a P value of 0.05 became enshrined as 'statistically significant', for example. “The P value was never meant to be used the way it's used today,” says Goodman. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:8e598073482e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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<item rdf:about="http://reganmian.net/blog/2014/10/14/starting-data-analysiswrangling-with-r-things-i-wish-id-been-told/">
    <title>Starting data analysis/wrangling with R: Things I wish I'd been told (Stian Haklev)</title>
    <dc:date>2014-11-25T15:01:36+00:00</dc:date>
    <link>http://reganmian.net/blog/2014/10/14/starting-data-analysiswrangling-with-r-things-i-wish-id-been-told/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:d453b9e41618/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://m.smx.sagepub.com/content/44/1/1.abstract">
    <title>Qualitative Comparative Analysis in Critical Perspective (Samuel R. Lucas, Alisa Szatrowski)</title>
    <dc:date>2014-10-17T13:57:26+00:00</dc:date>
    <link>http://m.smx.sagepub.com/content/44/1/1.abstract</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" the authors analyze several simulated data sets for which true causal processes are known. They find that QCA finds the correct causal story only 3 times across 70 different solutions, and even these rare successes, on closer examination, actually reveal additional fundamental problems with the method. Further epistemological analyses of the results find key problems with QCA’s stated epistemology, and results indicate that QCA fails even when its stated epistemological claims are ontologically accurate. Thus, the authors conclude that analysts should reject both QCA and its epistemological justifications in favor of existing effective methods and epistemologies for qualitative research. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:356f010098ce/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://scatter.wordpress.com/2014/10/06/big-data-hubris/">
    <title>Big Data Hubris (Andrew Perrin @ Scatterplot)</title>
    <dc:date>2014-10-07T02:10:07+00:00</dc:date>
    <link>http://scatter.wordpress.com/2014/10/06/big-data-hubris/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:3e8771a9cf7f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://cat-help.qdap.net/Coding%20Styles.ashx">
    <title>Coding Analysis Toolkit - coding styles</title>
    <dc:date>2014-02-13T16:34:26+00:00</dc:date>
    <link>http://cat-help.qdap.net/Coding%20Styles.ashx</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:765614a37d15/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.refsmmat.com/statistics/">
    <title>Statistics Done Wrong</title>
    <dc:date>2013-10-30T17:12:09+00:00</dc:date>
    <link>http://www.refsmmat.com/statistics/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:559e33e977e8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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<item rdf:about="http://7ds.parusanalytics.com/">
    <title>Seven Deadly Sins of Quantitative Analysis (Philip A. Schrodt)</title>
    <dc:date>2013-08-02T17:15:56+00:00</dc:date>
    <link>http://7ds.parusanalytics.com/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:37a93369ab87/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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<item rdf:about="http://research.stowers-institute.org/efg/R/Color/Chart/">
    <title>Chart of R Colors (Earl F. Glynn | Stowers Institute for Medical Research)</title>
    <dc:date>2013-06-26T15:55:49+00:00</dc:date>
    <link>http://research.stowers-institute.org/efg/R/Color/Chart/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:c084be032acf/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://plover.net/~bonds/cultofbayes.html">
    <title>The Cult of Bayes' Theorem</title>
    <dc:date>2013-05-12T20:34:59+00:00</dc:date>
    <link>http://plover.net/~bonds/cultofbayes.html</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" In general practice, there's no way to come up with meaningful figures for the right-hand side of the Bayes equation, and so Bayesians inevitably end up choosing values that happen to justify their existing beliefs. "]]></description>
<dc:subject>data-analysis singularitarianism</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:2531b2a61b19/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:singularitarianism"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://xkcd.com/1047/">
    <title>Approximations (xkcd)</title>
    <dc:date>2013-03-22T21:38:23+00:00</dc:date>
    <link>https://xkcd.com/1047/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:091b908b395e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.journaliststoolbox.org/">
    <title>Journalist's Toolbox</title>
    <dc:date>2012-06-16T00:47:39+00:00</dc:date>
    <link>http://www.journaliststoolbox.org/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>journalism data-analysis</dc:subject>
<dc:source>https://apple.com/iphone/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:eedb9af11c9d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:journalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
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</item>
<item rdf:about="http://www.badscience.net/2012/03/is-there-statistical-evidence-of-fraud-in-the-russian-election-data/">
    <title>Is there statistical evidence of fraud in the Russian election data? (Ben Goldacre | Bad Science)</title>
    <dc:date>2012-03-05T17:30:33+00:00</dc:date>
    <link>http://www.badscience.net/2012/03/is-there-statistical-evidence-of-fraud-in-the-russian-election-data/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[Shorter: Stata fun but wrong tool.]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:source>https://twitter.com/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:8b06e6619b2e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://codeandculture.wordpress.com/2011/10/04/adding-elements-to-graphs-as-a-slideshow/">
    <title>Adding elements to graphs as a slideshow (Gabriel Rossman @ Code and Culture)</title>
    <dc:date>2011-10-04T15:18:59+00:00</dc:date>
    <link>https://codeandculture.wordpress.com/2011/10/04/adding-elements-to-graphs-as-a-slideshow/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" The basic trick is that Stata can create transparent graph elements by setting the color to “none”. You do the exact same graph multiple times, you just set colors to be transparent when you want to conceal elements. That is, the code in lines 10–14 is identical to that in lines 17–21 except that lines 13 and 14 set line color to “none” instead of Stata’s standard s2color scheme. "]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:c97e08248bef/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://betterexplained.com/articles/demystifying-the-natural-logarithm-ln/">
    <title>Demystifying the Natural Logarithm (Kalid Azad @ BetterExplained)</title>
    <dc:date>2011-07-23T20:14:33+00:00</dc:date>
    <link>http://betterexplained.com/articles/demystifying-the-natural-logarithm-ln/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:7cacdb5d432d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://betterexplained.com/articles/an-intuitive-guide-to-exponential-functions-e/">
    <title>An Intuitive Guide To Exponential Functions (Kalid Azad @ BetterExplained)</title>
    <dc:date>2011-07-20T21:50:57+00:00</dc:date>
    <link>http://betterexplained.com/articles/an-intuitive-guide-to-exponential-functions-e/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:5a3899196e09/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.survey-design.com.au/Usergraphs.html">
    <title>User written Stata graph commands</title>
    <dc:date>2011-07-13T18:58:58+00:00</dc:date>
    <link>http://www.survey-design.com.au/Usergraphs.html</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:c592b2703ef4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.guardian.co.uk/technology/blog/2011/jun/28/lulzsec-hacking-analysed-relationships">
    <title>LulzSec chatlogs analysed: who talked to who, and when (Josh Halliday, The Guardian)</title>
    <dc:date>2011-06-28T15:59:55+00:00</dc:date>
    <link>http://www.guardian.co.uk/technology/blog/2011/jun/28/lulzsec-hacking-analysed-relationships</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[unspecified social network methods ostensibly applied to 5 days of LulzSec chat logs]]></description>
<dc:subject>Anonymous data-analysis AntiSec</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:930b7cc3c835/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:Anonymous"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:AntiSec"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.niemanlab.org/2011/06/deeper-into-data-u-k-based-scraperwiki-plans-new-tools-and-u-s-expansion-with-news-challenge/">
    <title>Deeper into data: U.K-based ScraperWiki plans new tools and U.S. expansion with News Challenge (Justin Ellis @ Nieman Journalism Lab)</title>
    <dc:date>2011-06-27T18:32:46+00:00</dc:date>
    <link>http://www.niemanlab.org/2011/06/deeper-into-data-u-k-based-scraperwiki-plans-new-tools-and-u-s-expansion-with-news-challenge/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>journalism data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:eab3e7bdc2df/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:journalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.comstockfilms.com/blog/tony/2009/02/25/harvards-benjamin-edelman-latest-to-be-suckered-by-avns-12byear-figure/">
    <title>Harvard’s Benjamin Edelman latest to be suckered by AVN’s $12B/year Figure (Tony Comstock)</title>
    <dc:date>2011-02-12T22:08:32+00:00</dc:date>
    <link>http://www.comstockfilms.com/blog/tony/2009/02/25/harvards-benjamin-edelman-latest-to-be-suckered-by-avns-12byear-figure/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" Anyway, the $12/B figure is in print again. This time in a journal published by the American Economic Association. Never mind the only place the figure has ever appeared as original data is in the ever reliable AVN, and AVN’s source is (when asked by an enterprising Forbes reporter) “a pie chart.” "]]></description>
<dc:subject>data-analysis failure academia</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:00fb33480435/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:failure"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:academia"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.theatlantic.com/culture/archive/2011/02/is-that-a-boiled-frog-in-your-pocket-or-are-you-just-happy-to-see-me/70638/">
    <title>Is That a Boiled Frog in Your Pocket? Or Are You Just Happy to See Me? (Tony Comstock @ The Atlantic)</title>
    <dc:date>2011-02-12T18:59:24+00:00</dc:date>
    <link>http://www.theatlantic.com/culture/archive/2011/02/is-that-a-boiled-frog-in-your-pocket-or-are-you-just-happy-to-see-me/70638/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[" Are we really supposed to believe that, despite the fact that we can't find evidence of any meaningful amount of money, there's a vast network of Lex Luther-like porn moguls, living inside underground lairs, filled with stolen antiquities? Or is it something more like China, hysteria, fear, and titillation that leaves common sense and observable facts behind?  "]]></description>
<dc:subject>journalism failure data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:0d136ec7b64d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:journalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:failure"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://bactra.org/weblog/727.html">
    <title>Writing R Functions (Advanced Data Analysis from an Elementary Point of View) (crshalizi @ Three-Toed Sloth)</title>
    <dc:date>2011-02-08T19:03:04+00:00</dc:date>
    <link>http://bactra.org/weblog/727.html</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:4f1a33b91c3c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://theatlantic.com/international/archive/2011/02/crowdsourcing-china-labor-strikes/70883/">
    <title>Crowdsourcing China Labor Strikes (Ella Chou, The Atlantic)</title>
    <dc:date>2011-02-07T23:41:38+00:00</dc:date>
    <link>http://theatlantic.com/international/archive/2011/02/crowdsourcing-china-labor-strikes/70883/</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>data-analysis protest</dc:subject>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:e03cd3756991/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:protest"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.apps.chicagotribune.com/2011/01/28/steal-this-code-the-newsapps-boundary-service-api/">
    <title>Steal this code: The Newsapps Boundary Service API! (Christopher Groskopf @ News Apps Blog)</title>
    <dc:date>2011-01-29T17:31:50+00:00</dc:date>
    <link>http://blog.apps.chicagotribune.com/2011/01/28/steal-this-code-the-newsapps-boundary-service-api/</link>
    <dc:creator>kellyramsey</dc:creator><description><![CDATA[GIS boundaries with an Illinois example]]></description>
<dc:subject>data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:3badc0556a89/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.propublica.org/nerds/item/doc-dollars-guides-collecting-the-data">
    <title>Scraping for Journalism: A Guide for Collecting Data (ProPublica)</title>
    <dc:date>2011-01-21T22:28:03+00:00</dc:date>
    <link>http://www.propublica.org/nerds/item/doc-dollars-guides-collecting-the-data</link>
    <dc:creator>kellyramsey</dc:creator><dc:subject>journalism data-analysis</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:kellyramsey/b:e7f8ed12770f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:journalism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:kellyramsey/t:data-analysis"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>