Bayesian inference is a statistical method that applies Bayes' theorem to update the probability of a hypothesis based on new evidence or data. It is grounded in the principles of Bayesian statistics, which interpret probability as a measure of belief or certainty rather than a frequency of occurrence. ### Key Components: 1. **Prior Probability (Prior):** This is the initial belief about a hypothesis before observing any data. It reflects the information or assumptions we have prior to the analysis.
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