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 ...

This is a guest post by Nathan Paxton. As social scientists, at least as regards what we can empirically assess, we tend to make statements of probability rather than fact. So rather than say that ...

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 ...

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

Pediatric clinical trials commonly experience recruitment challenges including limited number of patients and investigators, inclusion/exclusion criteria that further reduce the patient pool, and a ...

Get your news from a source that’s not owned and controlled by oligarchs. Sign up for the free Mother Jones Daily. It is really, really hard to find stuff to write about other than the C19 pandemic.

A common misconception about Bayesian statistics is that it mainly involves incorporating personal prior beliefs or subjective opinions. While priors do play a role, the core strength of Bayesian ...

The aim of Statistical Science is to present the full range of contemporary statistical thought at a technical level accessible to the broad community of practitioners, teachers, researchers, and ...