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Bayesian analysis is a type of statistical inference that views probabilities as the likelihood of an event happening. It differs from classical (frequentist) statistics in that probabilities are treated as degrees of belief, rather than frequencies. These beliefs can be updated as new data is acquired. The result is a posterior distribution. This represents the hypothesis’ updated probabilities based on the data and prior information.