Manish Ravi

@manish-ecol.bsky.social

PhD candidate @BEElab @IISER-TVM Plant-Insect interactions | Insect Diversity | Pollination | Landscapes | Ecology (He/Him)

Most of the statistical tests you learned in stats class — t-test, ANOVA, correlation — are actually special cases of a single thing: linear regression. Ch 7 of Experimentology argues that thinking in models, not tests, is more flexible and a better foundation for theory. 🧵 experimentology.io

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Knowing even a little bit of how DAGs work, and tiny pieces of causal inference can mean...you suddenly realise some (new and old) 'big' papers in your field arent really showing what they claim..even if there is a 'positive' signal...sigh...

These claims about what AI can do truly need citations. Checking statistics isn’t routine work, nor is whether citations to the literature are sensible. Whether statistics are appropriate and render reasonable inferences is inherently a question of human judgement.

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Nature Portfolio@natureportfolio.nature.com · 9mo ago

“The noise in human peer reviews is crucial because it arises from the variability in human experience and practical knowledge — two features that no model’s training corpus can fully capture,” writes Giorgio F. Gilestro in Nature about the introduction of AI peer reviews. #Academicsky 🧪

Learned today that “Galápagos” comes from a Spanish word for tortoise, meaning that “Galápagos Tortoise” is, in fact, a tortology

Fitting a generalized mixed model with a gamma distribution log link and random slopes to reaction time data to arrive at precisely the same point estimate as the authors did by simply averaging and conducting a t-test:

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