 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.