Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

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

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 ...

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 ...

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 ...

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 ...

It turns out that the old adage about statistics and damned lies wasn’t a joke. Sticks and stones may be bonebreakers, and words inflict no (physical) pain, but numbers can kill. In 2004, for instance ...

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 ...