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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.

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After reading about the bayesian approach, I'm wondering how they would interpret a null finding from a regression coefficient. I ask because in a frequentist approach, if the p<.05 you'd say that … shoe size, b=.05, p=.40. Now in the bayesian context, it seems like there's no easy way to describe associations. Maybe, if using something like a credible interval to describe the posterior …
asked Aug 23 '18 by Emma