Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

The FDA has released draft guidance on how sponsors can use Bayesian models for clinical trials.

Offered through an interdisciplinary partnership, data science at CU Boulder is delivered by the Departments of Applied Mathematics, Computer Science, and Information Science and awarded by the ...

In this video from PyCon Australia, Rhydwyn McGuire from the The New South Wales Department of Health presents: Video: Fast, Beautiful and Easy Bayesian Modeling – Can You have it all? Bayesian models ...

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 ...

News consumers often encounter visualizations through data journalism about topics like climate change or election results – topics where people bring their own background knowledge and beliefs when ...

Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...

Introduction Cerebral palsy (CP) is a non-progressive condition involving movement and muscle tone difficulties due to injury to the developing brain. Most cases arise around birth, but a smaller ...