Category: Statistics

Postdocs and Research fellows for combining probabilistic programming, simulators and interactive AI

Here’s a great opportunity for those interested in probabilistic programming and workflows for Bayesian data analysis: We (including me, Aki) are looking for outstanding postdoctoral researchers and research fellows to work for a new exciting project in the crossroads of probabilistic programming, simulator-based inference and user interfaces. You will have an opportunity to work with […]

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“Statistical and Machine Learning forecasting methods: Concerns and ways forward”

Roy Mendelssohn points us to this paper by Spyros Makridakis, Evangelos Spiliotis, and Vassilios Assimakopoulos, which begins: Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose […]

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The purported CSI effect and the retroactive precision fallacy

Regarding our recent post on the syllogism that ate science, someone points us to this article, “The CSI Effect: Popular Fiction About Forensic Science Affects Public Expectations About Real Forensic Science,” by N. J. Schweitzer and Michael J. Saks. We’ll get to the CSI Effect in a bit, but first I want to share the […]

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Cornell prof (but not the pizzagate guy!) has one quick trick to getting 1700 peer reviewed publications on your CV

From the university webpage: Robert J. Sternberg is Professor of Human Development in the College of Human Ecology at Cornell University. . . . Sternberg is the author of over 1700 refereed publications. . . . How did he compile over 1700 refereed publications? Nick Brown tells the story: I [Brown] was recently contacted by […]

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“We are reluctant to engage in post hoc speculation about this unexpected result, but it does not clearly support our hypothesis”

Brendan Nyhan and Thomas Zeitzoff write: The results do not provide clear support for the lack-of control hypothesis. Self-reported feelings of low and high control are positively associated with conspiracy belief in observational data (model 1; p

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“Simulations are not scalable but theory is scalable”

Eren Metin Elçi writes: I just watched this video the value of theory in applied fields (like statistics), it really resonated with my previous research experiences in statistical physics and on the interplay between randomised perfect sampling algorithms and Markov Chain mixing as well as my current perspective on the status quo of deep learning. […]

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My two talks in Austria next week, on two of your favorite topics!

Innsbruck, 7 Nov 2018: The study of American politics as a window into understanding uncertainty in science We begin by discussing recent American elections in the context of political polarization, and we consider similarities and differences with European politics. We then discuss statistical challenges in the measurement of public opinion: inference from opinion polls with […]

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“What Happened Next Tuesday: A New Way To Understand Election Results”

Yair just published a long post explaining (a) how he and his colleagues use Mister P and the voter file to get fine-grained geographic and demographic estimates of voter turnout and vote preference, and (b) why this makes a difference. The relevant research paper is here. As Yair says in his above-linked post, he and […]

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Facial feedback: “These findings suggest that minute differences in the experimental protocol might lead to theoretically meaningful changes in the outcomes.”

Fritz Strack points us to this article, “When Both the Original Study and Its Failed Replication Are Correct: Feeling Observed Eliminates the Facial-Feedback Effect,” by Tom Noah, Yaacov Schul, and Ruth Mayo, who write: According to the facial-feedback hypothesis, the facial activity associated with particular emotional expressions can influence people’s affective experiences. Recently, a replication […]

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Raghuveer Parthasarathy’s big idea for fixing science

Raghuveer Parthasarathy writes: The U.S. National Science Foundation ran an interesting call for proposals recently called the “Idea Machine,” aiming to gather “Big Ideas” to shape the future of research. It was open not just to scientists, but to anyone interested in potentially identifying grand challenges and new directions. He continues: (i) There are non-obvious, […]

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“2010: What happened?” in light of 2018

Back in November 2010 I wrote an article that I still like, attempting to answer the question: “How could the voters have swung so much in two years? And, why didn’t Obama give Americans a better sense of his long-term economic plan in 2009, back when he still had a political mandate?” My focus was […]

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Explainable ML versus Interpretable ML

First, I (Keith) want to share something I was taught in MBA school –  all new (and old but still promoted) technologies exaggerate their benefits, are overly dismissive of difficulties, underestimate the true costs and fail to anticipate how older (less promoted) technologies can adapt and offer similar and/or even better benefits and/or with less […]

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What does it mean to talk about a “1 in 600 year drought”?

Patrick Atwater writes: Curious to your thoughts on a bit of a statistical and philosophical quandary. We often make statements like this drought was a 1 in 400 year event but what do we really mean when we say that? In California for example there was an oft repeated line that the recent historic drought was […]

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