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Bayesian statistics is a branch of statistics that incorporates prior knowledge or beliefs into the analysis of data. It is based on Bayes' theorem, which describes how to update the probability of a hypothesis as more evidence or information becomes available. The core components of Bayesian statistics include: 1. **Prior Distribution**: This represents the initial beliefs or knowledge about a parameter before observing any data.

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  1. Conditional probability
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