Likelihood functions are mathematical functions that measure how well a statistical model explains observed data based on specific parameters. They play a crucial role in Bayesian statistics, where they help update prior beliefs about parameters in light of new data. Understanding likelihood functions is essential for analyzing independence between variables and is also pivotal in Bayesian model averaging, where they guide the selection of models based on their explanatory power regarding the observed data.
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