Bayesian modeling

Bayesian modeling is a statistical approach that uses Bayes’ theorem to update beliefs about parameters in a statistical model as new data becomes available. It combines prior knowledge (expressed as a prior distribution) with observed data to obtain a posterior distribution, which then informs predictions and decision-making. This framework is flexible, can handle uncertainty and missing data effectively, and is applicable across diverse fields.

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