Bayesian Statistics

Bayesian statistics is a branch of statistics that deals with the interpretation of probability as a measure of uncertainty in the presence of incomplete knowledge or uncertainty. It provides a framework for updating beliefs or probabilities based on new data or evidence. In Bayesian statistics, prior knowledge or beliefs about a parameter or hypothesis are combined with observed data to obtain a posterior distribution, which represents the updated knowledge or beliefs. Bayesian statistics is widely used in machine learning, data analysis, and artificial intelligence, particularly in applications where the amount of data is limited or the model is complex. It allows for the incorporation of prior knowledge or assumptions into the analysis, which can improve the accuracy and robustness of the results.
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