Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

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 ...

The main focus of this short course will be the Bayesian aspect of it. That means this is a slightly more advanced course requiring some knowledge of basic probability, regression methods, and the R ...

Get your news from a source that’s not owned and controlled by oligarchs. Sign up for the free Mother Jones Daily. It is really, really hard to find stuff to write about other than the C19 pandemic.

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 ...

David Vaux argues that experimental biologists should be better versed in classical statistics (Nature 492, 180–181; 2012). We suggest that they might also join the shift to Bayesian statistics that ...

Statistical Science, Vol. 26, No. 2, Special Issue on Bayesian Methods That Frequentists Should Know (May 2011), pp. 162-174 (13 pages) It is argued that the Calibrated Bayesian (CB) approach to ...