andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1277 knowledge-graph by maker-knowledge-mining

1277 andrew gelman stats-2012-04-23-Infographic of the year


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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.


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 What really makes it work, I think, is that it goes slowly enough. [sent-2, score-0.519]

2 2 minutes and 45 seconds is enough time for me, as a viewer, to feel like I’m living through each stage of development. [sent-3, score-1.397]

3 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. [sent-4, score-1.924]


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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.

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Introduction: 10,000 iterations for 4 chains on the (precompiled) efficiently-parameterized 8-schools model: > date () [1] "Thu Aug 30 22:12:53 2012" > fit3 <- stan (fit=fit2, data = schools_dat, iter = 1e4, n_chains = 4) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 1). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 2). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 3). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 4). Iteration: 10000 / 10000 [100%] (Sampling) > date () [1] "Thu Aug 30 22:12:55 2012" > print (fit3) Inference for Stan model: anon_model. 4 chains: each with iter=10000; warmup=5000; thin=1; 10000 iterations saved. mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat mu 8.0 0.1 5.1 -2.0 4.7 8.0 11.3 18.4 4032 1 tau 6.7 0.1 5.6 0.3 2.5 5.4 9.3 21.2 2958 1 eta[1] 0.4 0.0 0.9 -1.5 -0

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