This course covers the ideas underlying statistical modelling in science through the lens of causal thinking. We cover the implementation of these ideas through Bayesian computational methods and ...

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 ...

We review Bayesian approaches to model testing in general and to the assessment of topological hypotheses in particular. We show that the standard way of setting up Bayes factor tests of the monophyly ...

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

Regular Bayesian and frequentist approximations in statistics are studied within a unified framework. In particular it is shown how some higher-order likelihood-based approximations arise from their ...

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...

Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American I’m not sure when I first heard of Bayes’ ...