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 ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

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

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 76, No. 5 (NOVEMBER 2014), pp. 833-859 (27 pages) The choice of the summary statistics that are used in Bayesian ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

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 ...

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.

Bayes’s core contribution, which Chivers skillfully renders into cogent prose designed to educate the lay reader, is the notion that the likelihood of an event taking place in the future depends, in ...