In this paper, we show that the conditional frequentist method of testing a precise hypothesis can be made virtually equivalent to Bayesian testing. The conditioning strategy proposed by Berger, Brown ...

What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better decisions.

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Statistical Science, Vol. 26, No. 2, Special Issue on Bayesian Methods That Frequentists Should Know (May 2011), pp. 162-174 (13 pages) It is argued that the Calibrated Bayesian (CB) approach to ...

This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...

It turns out that the old adage about statistics and damned lies wasn’t a joke. Sticks and stones may be bonebreakers, and words inflict no (physical) pain, but numbers can kill. In 2004, for instance ...

One of the goals of statistics is to make inferences about population parameters from a limited set of observations. Last month, we showed how Bayes' theorem is used to update probability estimates as ...