andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-429 knowledge-graph by maker-knowledge-mining

429 andrew gelman stats-2010-11-24-“But you and I don’t learn in isolation either”


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Introduction: Indeed.


Summary: the most important sentenses genereted by tfidf model

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Introduction: Indeed.

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Introduction: Indeed.

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Introduction: Jeremy Fox points us to this compilation of data visualizations in R that went wrong, in a way that ended up making them look like art. They are indeed wonderful.

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Introduction: Basbøll : My aim is Socratic. I don’t want to help you become more knowledgeable. I want to help you better distinguish what you know from what you don’t know. Excellent point. Indeed, laying out what I do know and tracing the boundary of my ignorance, that’s what writing is all about for me.

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Introduction: Leading theoretical statistician Larry Wassserman in 2008 : Some of the greatest contributions of statistics to science involve adding additional randomness and leveraging that randomness. Examples are randomized experiments, permutation tests, cross-validation and data-splitting. These are unabashedly frequentist ideas and, while one can strain to fit them into a Bayesian framework, they don’t really have a place in Bayesian inference. The fact that Bayesian methods do not naturally accommodate such a powerful set of statistical ideas seems like a serious deficiency. To which I responded on the second-to-last paragraph of page 8 here . Larry Wasserman in 2013 : Some people say that there is no role for randomization in Bayesian inference. In other words, the randomization mechanism plays no role in Bayes’ theorem. But this is not really true. Without randomization, we can indeed derive a posterior for theta but it is highly sensitive to the prior. This is just a restat

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15 0.079687886 999 andrew gelman stats-2011-11-09-I was at a meeting a couple months ago . . .

16 0.07967338 376 andrew gelman stats-2010-10-28-My talk at American University

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Introduction: Indeed.

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Introduction: Indeed.

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Introduction: Jeremy Fox points us to this compilation of data visualizations in R that went wrong, in a way that ended up making them look like art. They are indeed wonderful.

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Introduction: Basbøll : My aim is Socratic. I don’t want to help you become more knowledgeable. I want to help you better distinguish what you know from what you don’t know. Excellent point. Indeed, laying out what I do know and tracing the boundary of my ignorance, that’s what writing is all about for me.

5 0.34238216 676 andrew gelman stats-2011-04-23-The payoff: $650. The odds: 1 in 500,000.

Introduction: Details here .

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Introduction: Indeed.

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Introduction: Indeed.

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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.

4 0.40671077 1654 andrew gelman stats-2013-01-04-“Don’t think of it as duplication. Think of it as a single paper in a superposition of two quantum journals.”

Introduction: Adam Marcus at Retraction Watch reports on a physicist at the University of Toronto who had this unfortunate thing happen to him: This article has been retracted at the request of the Editor-in-Chief and first and corresponding author. The article was largely a duplication of a paper that had already appeared in ACS Nano, 4 (2010) 3374–3380, http://dx.doi.org/10.1021/nn100335g. The first and the corresponding authors (Kramer and Sargent) would like to apologize for this administrative error on their part . . . “Administrative error” . . . I love that! Is that what the robber says when he knocks over a liquor store and gets caught? As Marcus points out, the two papers have different titles and a different order of authors, which makes it less plausible that this was an administrative mistake (as could happen, for example, if a secretary was given a list of journals to submit the paper to, and accidentally submitted it to the second journal on the list without realizing it

5 0.33349743 1055 andrew gelman stats-2011-12-13-Data sharing update

Introduction: Fred Oswald reports that Sian Beilock sent him sufficient amounts of raw data from her research study so allow him to answer his questions about the large effects that were observed. This sort of collegiality is central to the collective scientific enterprise. The bad news is that IRB’s are still getting in the way. Beilock was very helpful but she had to work within the constraints of her IRB, which apparently advised her not to share data—even if de-identified—without getting lots more permissions. Oswald writes: It is a little concerning that the IRB bars the sharing of de-identified data, particularly in light of the specific guidelines of the journal Science, which appears to say that when you submit a study to the journal for publication, you are allowing for the sharing of de-identified data — unless you expressly say otherwise at the point that you submit the paper for consideration. Again, I don’t blame Beilock and Ramirez—they appear to have been as helpful as

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