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 ...

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 ...

Above is a simulated charge sensor signal and its histogram. Below is a time integration that reduces noise and enables state identification (called threshold judgment, a conventional method). A ...

A research team at Tohoku University's Advanced Institute for Materials Research (WPI-AIMR) has developed a new technique to rapidly and accurately determine the charge state of electrons confined in ...

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WASHINGTON, Jan. 20, 2026 /PRNewswire/ -- The U.S. Food and Drug Administration (FDA) has issued new draft guidance modernizing statistical methodologies used in clinical trials, formally recognizing ...

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

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 ...