In the 20th-century statistics wars, Bayesians were underdogs. Now their methods may help speed treatments to market.

Bayesian statistics represents a powerful framework for data analysis that centres on Bayes’ theorem, enabling researchers to update existing beliefs with incoming evidence. By combining prior ...

With so many worlds out there, the question is: How many are home to advanced life? In a paper just published in the Proceedings of the National Academy of Sciences, David Kipping from Columbia ...

We discuss the development of a course in Bayesian statistics that began as an offering to statistics graduate students, evolved into a course for graduate students in other departments, then was ...

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...

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 ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

The primary goal of the trial was to optimize radiation therapy (RT) dose among three levels (low, standard, and high), given either with placebo (P) or an investigational agent (A), for treating ...