A researcher computes both a frequentist confidence interval, and a Bayesian credible interval. After the computation, the researcher realizes that the credible interval is much more narrow than the confidence interval. What could be a reason why this happened?
An analyst conducts both a Bayesian hypothesis test (using Bayes Factors) and classic NHST (using p-values). The Bayesian results indicate weak support for the null hypothesis, but the p-value is small, indicating that the null should be rejected. Consider a reason why this could happen.
We have discussed four ways of statistical inference in class (NHST, Confidence Intervals, Bayes Factors, Credible Intervals). For each of these four methods, describe BRIEFLY (one or two sentences) two advantages and two disadvantages. You can list reasons that we have covered in class, or you can be creative and anticipate certain problems or benefits of the methods.