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 ...

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 ...

A probability is a number that takes some value equal to or between zero and one. If the probability of the 'event' of interest is zero, then the event cannot occur. So, for example, the probability ...

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

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), ...

Functional safety engineers follow the ISA/IEC 61511 standard and perform calculations based on random hardware failures. These result in very low failure probabilities, which are then combined with ...

Regina Nuzzo gives a fair account of the conflicts between frequentist and Bayesian statistics (14 March, p 38), and I agree with the conclusion that applied statisticians generally combine both ...