= Conjugate prior distributions
{wiki=Category:Conjugate_prior_distributions}
In Bayesian statistics, a conjugate prior distribution is a prior distribution that, when used in conjunction with a specific likelihood function, results in a posterior distribution that is in the same family as the prior distribution. This property greatly simplifies the process of updating beliefs in light of new evidence. \#\#\# Key Concepts: 1. **Prior Distribution**: This represents the initial beliefs about a parameter before observing any data. In Bayesian analysis, one needs to specify this prior.
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