This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

Journal of Computational and Graphical Statistics, Vol. 19, No. 2 (June 2010), pp. 260-280 (21 pages) We describe a strategy for Markov chain Monte Carlo analysis of nonlinear, non-Gaussian ...

We’ll discuss some basic concepts and vocabulary in Bayesian statistics such as the likelihood, prior and posterior distributions, and how they relate to Bayes’ Rule. R statistical software will be ...

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

The European Medicines Agency (EMA) has begun a consultation into the use of Bayesian methods in the analysis of clinical trial data. Bayesian methods are one of the main approaches to statistical ...

A collaboration including the University of Oxford, University of British Columbia, Intel, New York University, CERN, and the National Energy Research Scientific Computing Center is working to make it ...

A research team has developed a new technique to rapidly and accurately determine the charge state of electrons confined in semiconductor quantum dots -- fundamental components of quantum computing ...

WASHINGTON, Jan. 20, 2026 /PRNewswire/ -- The U.S. Food and Drug Administration (FDA) has issued new draft guidance modernizing statistical methodologies used in clinical trials, formally recognizing ...

Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

Scientists have quantified what draws mosquitoes to people—which could help make better, life-saving bug traps.