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 ...

You're sitting in the doctor's office waiting for the result of a test. The test will tell you whether you have a disease you really don't want to have. As you wait, it seems as if the whole world is ...

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 ...

Bernoulli’s 1713 golden theorem is viewed retrospectively in the context of modern model-based frequentist inference that revolves around the concept of a prespecified statistical model Mθ (x), ...

WE ARE in a bar, and agree to toss a coin for the next round. Heads, I pay; tails, the drinks are on you. What are your chances of a free pint? Most people – sober ones, at least – would agree: ...

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 ...

Bayes’s core contribution, which Chivers skillfully renders into cogent prose designed to educate the lay reader, is the notion that the likelihood of an event taking place in the future depends, in ...