andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2034 knowledge-graph by maker-knowledge-mining
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Introduction: Philosophie et practique de la statistique bayésienne . I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. P.S. For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). {\em British Journal of Mathematical and Statistical Psychology} {\bf 66}, 8–18. (Andrew Gelman and Cosma Shalizi) [2013] Rejoinder to discussion. (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should)
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1 I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. [sent-2, score-0.204]
2 The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. [sent-3, score-0.344]
3 For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). [sent-6, score-0.15]
4 (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. [sent-9, score-0.08]
5 {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should) They Meet In 2011 and Beyond? [sent-10, score-0.074]
6 (Andrew Gelman) and also these two recent papers on the importance of informative models in routine Bayesian inference: [2014] The connection between varying treatment effects and the crisis of unreplicable research: A Bayesian perspective. [sent-17, score-0.532]
7 (Andrew Gelman) [2012] P-values and statistical practice. [sent-19, score-0.065]
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same-blog 1 1.0000001 2034 andrew gelman stats-2013-09-23-My talk Tues 24 Sept at 12h30 at Université de Technologie de Compiègne
Introduction: Philosophie et practique de la statistique bayésienne . I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. P.S. For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). {\em British Journal of Mathematical and Statistical Psychology} {\bf 66}, 8–18. (Andrew Gelman and Cosma Shalizi) [2013] Rejoinder to discussion. (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should)
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Introduction: There’s lots of overlap but I put each paper into only one category. Also, I’ve included work that has been published in 2013 as well as work that has been completed this year and might appear in 2014 or later. So you can can think of this list as representing roughly two years’ work. Political science: [2014] The twentieth-century reversal: How did the Republican states switch to the Democrats and vice versa? {\em Statistics and Public Policy}. (Andrew Gelman) [2013] Hierarchical models for estimating state and demographic trends in U.S. death penalty public opinion. {\em Journal of the Royal Statistical Society A}. (Kenneth Shirley and Andrew Gelman) [2013] Deep interactions with MRP: Election turnout and voting patterns among small electoral subgroups. {\em American Journal of Political Science}. (Yair Ghitza and Andrew Gelman) [2013] Charles Murray’s {\em Coming Apart} and the measurement of social and political divisions. {\em Statistics, Politics and Policy}.
Introduction: The talk is at the University of Amsterdam in the Diamantbeurs (Weesperplein 4, Amsterdam), room 5.01, at noon. Here’s the plan: Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that are implausible and cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. I don’t know how organized this talk will be. It combines a bunch of ideas that have been floating around recently. Here are a few recent articles that
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Introduction: My article with Cosma Shalizi has appeared in the British Journal of Mathematical and Statistical Psychology. I’m so glad this paper has come out. I’d been thinking about writing such a paper for almost 20 years. What got me to actually do it was an invitation a few years ago to write a chapter on Bayesian statistics for a volume on the philosophy of social sciences. Once I started doing that, I realized I had enough for a journal article. I contacted Cosma because he, unlike me, was familiar with the post-1970 philosophy literature (my knowledge went only up to Popper, Kuhn, and Lakatos). We submitted it to a couple statistics journals that didn’t want it (for reasons that weren’t always clear ), but ultimately I think it ended up in the right place, as psychologists have been as serious as anyone in thinking about statistical foundations in recent years. Here’s the issue of the journal , which also includes an introduction, several discussions, and a rejoinder: Prior app
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Introduction: Deborah Mayo, Aris Spanos, and Kent Staley edited a special issue on the philosophy of Bayesian statistics for the journal Rationality, Markets and Morals. Here are the contents : David Cox and Deborah G. Mayo, “Statistical Scientist Meets a Philosopher of Science: A Conversation” Deborah G. Mayo, “Statistical Science and Philosophy of Science: Where Do/Should They Meet in 2011 (and Beyond)?” Stephen Senn, “You May Believe You Are a Bayesian But You Are Probably Wrong” Andrew Gelman, “ Induction and Deduction in Bayesian Data Analysis “ Jan Sprenger, “The Renegade Subjectivist: Jose Bernardo’s Objective Bayesianism” Aris Spanos. “Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation” David F. Hendry, “Empirical Economic Model Discovery and Theory Evaluation” Larry Wasserman, “Low Assumptions, High Dimensions” For some reason, not all the articles are yet online, but it says they’re coming soon. In the meantime, you ca
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same-blog 1 0.97095931 2034 andrew gelman stats-2013-09-23-My talk Tues 24 Sept at 12h30 at Université de Technologie de Compiègne
Introduction: Philosophie et practique de la statistique bayésienne . I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. P.S. For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). {\em British Journal of Mathematical and Statistical Psychology} {\bf 66}, 8–18. (Andrew Gelman and Cosma Shalizi) [2013] Rejoinder to discussion. (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should)
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Introduction: There’s lots of overlap but I put each paper into only one category. Also, I’ve included work that has been published in 2013 as well as work that has been completed this year and might appear in 2014 or later. So you can can think of this list as representing roughly two years’ work. Political science: [2014] The twentieth-century reversal: How did the Republican states switch to the Democrats and vice versa? {\em Statistics and Public Policy}. (Andrew Gelman) [2013] Hierarchical models for estimating state and demographic trends in U.S. death penalty public opinion. {\em Journal of the Royal Statistical Society A}. (Kenneth Shirley and Andrew Gelman) [2013] Deep interactions with MRP: Election turnout and voting patterns among small electoral subgroups. {\em American Journal of Political Science}. (Yair Ghitza and Andrew Gelman) [2013] Charles Murray’s {\em Coming Apart} and the measurement of social and political divisions. {\em Statistics, Politics and Policy}.
Introduction: The talk is at the University of Amsterdam in the Diamantbeurs (Weesperplein 4, Amsterdam), room 5.01, at noon. Here’s the plan: Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? In recent years, psychology and medicine have been rocked by scandals of research fraud. At the same time, there is a growing awareness of serious flaws in the general practices of statistics for scientific research, to the extent that top journals routinely publish claims that are implausible and cannot be replicated. All this is occurring despite (or perhaps because of?) statistical tools such as Type 1 error control that are supposed to restrict the rate of unreliable claims. We consider ways in which prior information and Bayesian methods might help resolve these problems. I don’t know how organized this talk will be. It combines a bunch of ideas that have been floating around recently. Here are a few recent articles that
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Introduction: “Ich glaube, dass die Wahrscheinlichkeitsrechnung das richtige Werkzeug zum Lösen solcher Probleme ist”, sagt Andrew Gelman , Statistikprofessor von der Columbia-Universität in New York. Wie oft aber derart knifflige Aufgaben im realen Leben auftauchen, könne er nicht sagen. Was fast schon beruhigend klingt. OK, fine.
Introduction: Deborah Mayo, Aris Spanos, and Kent Staley edited a special issue on the philosophy of Bayesian statistics for the journal Rationality, Markets and Morals. Here are the contents : David Cox and Deborah G. Mayo, “Statistical Scientist Meets a Philosopher of Science: A Conversation” Deborah G. Mayo, “Statistical Science and Philosophy of Science: Where Do/Should They Meet in 2011 (and Beyond)?” Stephen Senn, “You May Believe You Are a Bayesian But You Are Probably Wrong” Andrew Gelman, “ Induction and Deduction in Bayesian Data Analysis “ Jan Sprenger, “The Renegade Subjectivist: Jose Bernardo’s Objective Bayesianism” Aris Spanos. “Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation” David F. Hendry, “Empirical Economic Model Discovery and Theory Evaluation” Larry Wasserman, “Low Assumptions, High Dimensions” For some reason, not all the articles are yet online, but it says they’re coming soon. In the meantime, you ca
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Introduction: Philosophie et practique de la statistique bayésienne . I’ll try to update the slides a bit since a few years ago , to add some thoughts I’ve had recently about problems with noninformative priors, even in simple settings. The location of the talk will not be convenient for most of you, but anyone who comes to the trouble of showing up will have the opportunity to laugh at my accent. P.S. For those of you who are interested in the topic but can’t make it to the talk, I recommend these two papers on my non-inductive Bayesian philosophy: [2013] Philosophy and the practice of Bayesian statistics (with discussion). {\em British Journal of Mathematical and Statistical Psychology} {\bf 66}, 8–18. (Andrew Gelman and Cosma Shalizi) [2013] Rejoinder to discussion. (Andrew Gelman and Cosma Shalizi) [2011] Induction and deduction in Bayesian data analysis. {\em Rationality, Markets and Morals}, special topic issue “Statistical Science and Philosophy of Science: Where Do (Should)
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Introduction: Marty McKee at Wolfram Research appears to have a very very stupid colleague. McKee wrote to Christian Robert: Your article, “Evidence and Evolution: A review”, caught the attention of one of my colleagues, who thought that it could be developed into an interesting Demonstration to add to the Wolfram Demonstrations Project. As Christian points out, adapting his book review into a computer demonstration would be quite a feat! I wonder what McKee’s colleague could be thinking? I recommend that Wolfram fire McKee’s colleague immediately: what an idiot! P.S. I’m not actually sure that McKee was the author of this email; I’m guessing this was the case because this other very similar email was written under his name. P.P.S. To head off the inevitable comments: Yes, yes, I know this is no big deal and I shouldn’t get bent out of shape about it. But . . . Wolfram Research has contributed such great things to the world, that I hate to think of them wasting any money paying
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Introduction: Felix Salmon relates the story of an economics Nobel Prize winner getting paid by a hedge fund. It would all seems pretty silly—sort of like Coca-Cola featuring Michael Jordan in their ads—except that hedge funds are disreputable nowadays and so it seems vaguely sleazy for a scholar to trade on his academic reputation to make free money in this way. It falls roughly in the same category as that notorious b-school prof in Inside Job who got $125K for writing a b.s. report about the financial stability of Iceland—and then, when they came back to him later and asked how he could’ve written it, he basically said: Hey, I don’t know anything about Iceland, I was just taking their money! That said, if a hedge fund offered me $125K to sit on their board, I’d probably take it! It’s hard to turn down free money. Or maybe not, I don’t really know. So far, when companies have paid me $, it’s been to do something for them, to consult or give a short course. I’d like to think that if
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Introduction: In an ideal world, research articles would be open to criticism and discussion in the same place where they are published, in a sort of non-corrupt version of Yelp. What is happening now is that the occasional paper or research area gets lots of press coverage, and this inspires reactions on science-focused blogs. The trouble here is that it’s easier to give off-the-cuff comments than detailed criticisms. Here’s an example. It starts a couple years ago with this article by Ryota Kanai, Tom Feilden, Colin Firth, and Geraint Rees, on brain size and political orientation: In a large sample of young adults, we related self-reported political attitudes to gray matter volume using structural MRI. We found that greater liberalism was associated with increased gray matter volume in the anterior cingulate cortex, whereas greater conservatism was associated with increased volume of the right amygdala. These results were replicated in an independent sample of additional participants. Ou
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Introduction: 1. We Bayesian statisticians like to say there are three kinds of statisticians: a. Bayesians; b. People who are Bayesians but don’t realize it (that is, they act in coherence with some unstated probability); c. Failed Bayesians (that is, people whose inference could be improved by some attention to coherence). So, if a statistician does great work, we are inclined to claim this person for the Bayesian cause, even if he or she vehemently denies any Bayesian leanings. 2. In his autobiography, Bertrand Russell tells the story of when he went to prison for opposing World War 1: I [Russell] was much cheered on my arrival by the warden at the gate, who had to take particulars about me. He asked my religion, and I replied ‘agnostic.’ He asked how to spell it, and remarked with a sigh: “Well, there are many religions, but I suppose they all worship the same God.” This remark kept me cheerful for about a week. 3. In an op-ed today, Ross Douthat argues that celebrated a
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