Bioinformatics
Bayes' Theorem is a fundamental principle in probability theory that describes how to update the probability of a hypothesis based on new evidence. It combines prior knowledge with new data to provide a revised probability, allowing for better decision-making and inference in uncertain situations. This theorem is especially crucial in statistical inference, where it forms the backbone of Bayesian analysis, enabling the integration of prior beliefs and observed data.
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