andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1302 knowledge-graph by maker-knowledge-mining

1302 andrew gelman stats-2012-05-06-Fun with google autocomplete


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Introduction: Aleks points us to this idea of labeling for news.


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Aleks points us to this idea of labeling for news. [sent-1, score-1.319]


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tfidf for this blog:

wordName wordTfidf (topN-words)

[('labeling', 0.618), ('aleks', 0.583), ('news', 0.338), ('points', 0.248), ('us', 0.239), ('idea', 0.214)]

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Introduction: Antonio Rinaldi writes: Here in Italy an “hype” topic is the “staffetta tra generazioni”, handover between generations: since unemployment rate in young people is very high, someone in the government is thinking to encourage older people to anticipate their retirement to make more jobs available for youngs. I am not an economist and I don’t want to discuss the economic plausibility of such a possible measure. However, some economists deny its success simply on the basis of a correlation and regression analysis. You can see the charts used as “evidence” here: http://www.lavoce.info/per-una-vera-staffetta-generazionale/ and here: http://noisefromamerika.org/articolo/occupazione-ricambio-intergenerazionale. The first chart shows that there is no correlation between activity rate in older people and unemployment rate in younger people. The second chart shows that there is a positive linear regression (even if the author doesn’t speak of a casual relationship) between activity rate in

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Introduction: Ruth Rosenholtz of the department of Brain and Cognitive Science at MIT writes: We mostly do computational modeling of human vision. We try to do on the one hand the sort of basic science that fits in the human vision community, while on the other hand developing predictive models which might actually lend insight into design. Your talk resonated with me in part because of this paper [Do Predictions of Visual Perception Aid Design?, by Ruth Rosenholtz, Amal Dorai, and Rosalind Freeman]. We went into our study thinking that people would like to have a quantitative tool to help analyze designs. But what we concluded, somewhat anecdotally, was that its main use seemed to be as a conversation-starter, and a means of communicating ideas about the design. And the reason it seemed to work is that our visualizations were the right level of a “puzzle” — challenging enough to be a bit fun to work out. On another topic, check out the infographic from last weekend’s NYTimes ma

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