Comment by Andrew Gelman

Statistician and political scientist, Professor at Columbia University
It's not clear to me that Bayesian inference is the right way to attack this sort of problem.
AI Verified (Feb 3, 2025)
Like Share on X 1h ago
Policy proposals and claims
votes Against
Statement relation verification history AI Verified Report this

Statement relation comments

AI Verified Relevant: the source page is specifically about a Bayesian analysis of COVID-19 origins, and the quoted line is the author's stated reason for doubt—he says Bayesian inference may not be the right way to approach this problem because of issues like likelihood specification and composite hypotheses. That directly bears on whether Bayesian analysis is the right framework for settling the COVID-19 origins question and gives a clear likely non-support signal. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/)) · YouCongress gpt-5.4-2026-03-05 · 57min ago
Vote inference verification history Latest opinion AI Verified Report this

Vote answer comments

AI Verified The author leans against the statement, not for it: he writes, “It’s not clear to me that Bayesian inference is the right way to attack this sort of problem,” and the surrounding post explains his concern that the likelihood, hypotheses, and even what counts as data are hard to specify in COVID-origins analysis. That is skepticism about Bayesian analysis being the right framework here, even if not an absolute rejection. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/)) · YouCongress gpt-5.4-2026-03-05 · 56min ago

Quote authenticity verification history

Report this

Quote authenticity comments

AI Verified The source URL is fetchable and contains the exact sentence “It’s not clear to me that Bayesian inference is the right way to attack this sort of problem.” in the post body. The post is dated February 3, 2025 and is posted by “Andrew”; the linked author page identifies that author as Andrew Gelman. The stored quote text, attribution, date, and source URL are consistent with the source. ([statmodeling.stat.columbia.edu](https://statmodeling.stat.columbia.edu/2025/02/03/bayesian-analysis-of-origins-of-covid/)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
replying to Andrew Gelman