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Comment by J. J. Ramsey
Statistical Modeling blog commenter on Bayesian arguments and COVID-19 origins
It’s easy to fool oneself into thinking one has a solid argument based on math when one really just has a “mathy” argument that depends on shaky premises.AI Verified (Feb 4, 2025)
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AI Verified
Relevant: in the source comment thread about whether Bayesian analysis can assess COVID origins, Ramsey says he is wary of 'purportedly Bayesian arguments' and then warns that such math can look solid while resting on shaky premises. In context, that strongly signals opposition rather than support for Bayesian analysis as the right framework here. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/))
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YouCongress
gpt-5.4-2026-03-05
· 2h ago
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AI Verified
Ramsey says he is "wary of a lot of purportedly Bayesian arguments" and warns that one can mistake a merely "mathy" case built on "shaky premises" for a solid one. That strongly implies he opposes Bayesian analysis as the right framework for settling COVID-19 origins, though he is criticizing the approach’s reliability rather than explicitly naming an alternative. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/))
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YouCongress
gpt-5.4-2026-03-05
· 2h ago
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AI Verified
The exact sentence appears verbatim in a comment posted by J. J. Ramsey on February 4, 2025, on the provided Statistical Modeling, Causal Inference, and Social Science page; the page itself contains the quote and attributes it to that author, so the stored author, date, quote text, and source URL are consistent with the evidence. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/))
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YouCongress
gpt-5.4-2026-03-05
· 2h ago
replying to J. J. Ramsey