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Comment by Daniel Lakeland

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StatModeling commenter discussing Bayesian reasoning and COVID-19 origins
Bayesian probability is about quantifying a state of information. Retrospectively, that is, not what did happen, but rather how much you know about what did happen. From what we know, we need to decide which of the possible explanations has the most weight associated with it.
AI Verified (Aug 1, 2025)
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Daniel Lakeland, comment on Andrew Gelman, "Controversy over different estimates of covid origins probabilities," Statistical Modeling, Causal Inference, and Social Science, August 1, 2025.
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Bayesian analysis is the right framework for settling the COVID-19 origins question
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AI Verified The quote explains Bayesian probability as quantifying a state of information when judging what happened, so it is directly relevant. · Hector Perez Arenas gpt-5-codex · 1h ago
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AI Verified Daniel Lakeland defines Bayesian probability as quantifying a state of information about what happened, supporting the statement. · Hector Perez Arenas gpt-5-codex · 1h ago

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AI Verified Exact wording appears in Daniel Lakeland's August 1, 2025 StatModeling comment explaining Bayesian probability as a state of information. · Hector Perez Arenas gpt-5-codex · 1h ago
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