Non-informative priors are prior probability distributions used in Bayesian statistics that contain minimal or no specific information about the parameters being estimated. These priors aim to have a neutral influence on the posterior distribution, allowing the data to dominate the inference process. They serve as a starting point for Bayesian estimation when there is little prior knowledge available, enabling a more objective analysis of the data.
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