The competing narratives of scientific revolution

Back when we were reading Karl Popper’s Logic of Scientific Discovery and Thomas Kuhn’s Structure of Scientific Revolutions, who would’ve thought that we’d be living through a scientific revolution ourselves? Scientific revolutions occur on all scales, but here let’s talk about some of the biggies: 1850-1950: Darwinian revolution in biology, changed how we think about […]

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Let’s get hysterical

Following up on our discussion of hysteresis in the scientific community, Nick Brown points us to this article this article from 2014, “Excellence by Nonsense: The Competition for Publications in Modern Science,” by Mathias Binswanger, who writes: To ensure the efficient use of scarce funds, the government forces universities and professors, together with their academic […]

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The fallacy of the excluded middle — statistical philosophy edition

I happened to come across this post from 2012 and noticed a point I’d like to share again. I was discussing an article by David Cox and Deborah Mayo, in which Cox wrote: [Bayesians’] conceptual theories are trying to do two entirely different things. One is trying to extract information from the data, while the […]

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3 YEARS AGO (AUGUST 2015): MEMORY LANE

MONTHLY MEMORY LANE: 3 years ago: August 2015. I mark in red 3-4 posts that seem most apt for general background on key issues in this blog, excluding those reblogged recently[1], and in green up to 3 others of relevance to philosophy of statistics [2]. Posts that are part of a “unit” or a group count as one. August 2015 08/05 Neyman: Distinguishing […]

3 YEARS AGO (AUGUST 2015): MEMORY LANE

MONTHLY MEMORY LANE: 3 years ago: August 2015. I mark in red 3-4 posts that seem most apt for general background on key issues in this blog, excluding those reblogged recently[1], and in green up to 3 others of relevance to philosophy of statistics [2]. Posts that are part of a “unit” or a group count as one. August 2015 08/05 Neyman: Distinguishing […]

Three informal case studies: (1) Monte Carlo EM, (2) a new approach to C++ matrix autodiff with closures, (3) C++ serialization via parameter packs

Andrew suggested I cross-post these from the Stan forums to his blog, so here goes. Maximum marginal likelihood and posterior approximations with Monte Carlo expectation maximization: I unpack the goal of max marginal likelihood and approximate Bayes with MMAP and Laplace approximations. I then go through the basic EM algorithm (with a traditional analytic example […]

The post Three informal case studies: (1) Monte Carlo EM, (2) a new approach to C++ matrix autodiff with closures, (3) C++ serialization via parameter packs appeared first on Statistical Modeling, Causal Inference, and Social Science.