Thanks! My review was presumably too cryptic and reserved, but I do agree with the fact that the “paradox” is not a paradox, either at the frequentist/Bayesian interface or within the Bayesian paradigm itself. Most posts I published on that theme feed this argument.

]]>Radford’s comment provides the answer to your question!

]]>More typically, however, one doesn’t think that the mean is either exactly zero or is from some prior that is flat in the vicinity of zero. Instead, one usually thinks that there is a substantial probability for the mean to be close to zero, but not exactly equal to zero. This of course leads to a different Bayesian conclusion, which is again entirely intuitive if this prior corresponds to what you actually believe.

Either way, there is no problem. There is nothing to “resolve”.

]]>Hearing that a solution to Lindley’s paradox has been found by allowing the significance level to depend on the sample size should be a good stimulus for the rolling of eyes.

Also is Lindley’s paradox really asking to be resolved? Or does it just simply exist?

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