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Can’t those shameless little bullies just let scientists do their research in peace? If a hypothesis test is statistically significant and a result is published in a real journal, that should be enough for any self-styled skeptic. Can you imagine what might happen if any published result could be questioned—by anybody? You’d have serious psychology […]
The post Enough with the replication police appeared first on Statistical Modeling, Causal Inference, and Social
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For yesterday‘s contest I really really really wanted to pick John Waters. For one thing, of all the 64 people in the bracket, he’s the one I think I’d like to hear the most. For another, he’s still alive and just might conceivably be amused enough by this whole contest to come up from Baltimore […]
The post The round of 8 begins: Mark Twain (4) vs. Miguel de Cervantes (2); Carlin advances appeared first on Statistical Modeling, Causal Inference, and Social
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Mark Palko points to this report and writes: Putting aside my concerns with the “additional years of learning” metric (and I have a lot of them), I have the feeling that there’s something strange here or i’m missing something obvious. That jump from 3-year impact to 4-year seems excessive. The press release links to a […]
The post Time-release pedagogy?? appeared first on Statistical Modeling, Causal Inference, and Social Science.

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The bard of the suburbs wins yesterday‘s bout with another fine turn of phrase, this time brought to us in comments by Ethan: “Drinking a toast to the visible world, his impending disappearance from it be damned.” Updike, from “My Father’s Tears.” I want to hear from someone who can write like that about things […]
The post George Carlin (2) vs. John Waters (1); Updike advances appeared first on Statistical Modeling, Causal Inference, and Social
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Ethics decisions, like statistical inferences, are informative only if they’re not too easy or too hard. For the full story, read the whole thing.
The post How is ethics like logistic regression? appeared first on Statistical Modeling, Causal Inference, and Social Science.