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  "body": "\n## Summary\n\nA Bayesian hierarchical model specifies a [[prior|00NBBSXRQS]] in several stages.\nThe parameters of the data model have a prior, and that prior has unknown hyperparameters with their own hyperprior.\nIt describes data in related groups, whose parameters are different but drawn from a common population.\nIts [[posterior|0KJ7ZS8AJA]] lets groups borrow strength from each other, and it is a fully Bayesian counterpart of the [[empirical Bayes method|8GG2Z2E61R]].\n\n## Explanations\n\n### L1 human\n\nThink of test scores in many schools.\nEach school has its own average level, but the schools are alike in many ways.\nA hierarchical model says: each school's level comes from a common distribution of levels, and the shape of that distribution is itself unknown.\nA small school with few scores then gets an estimate pulled towards the overall average, while a large school mostly keeps its own average.\n",
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