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Bayes linear statistics is an approach to statistical modeling and inference that combines principles of Bayesian statistics with a linear perspective on uncertainty. It focuses on updating beliefs in light of new evidence, and while it typically employs the structure of a Bayesian framework, it allows for a more intuitive interpretation of the uncertainty associated with parameters and predictions. ### Key Features of Bayes Linear Statistics: 1. **Linear Expectation**: Bayes linear statistics emphasizes the use of linear combinations of expectations.

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  1. Bayesian statistics
  2. Conditional probability
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