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 ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

WASHINGTON, Jan. 20, 2026 /PRNewswire/ -- The U.S. Food and Drug Administration (FDA) has issued new draft guidance modernizing statistical methodologies used in clinical trials, formally recognizing ...

Cobimetinib Plus Vemurafenib in Patients With Colorectal Cancer With BRAF Mutations: Results From the Targeted Agent and Profiling Utilization Registry (TAPUR) Study We divided the borrowing ...

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