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

A research team has now proposed an adaptive Bayesian sampling framework that significantly reduces data volume while ...

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 ...

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 ...

Members of the university community are invited to participate in a workshop on "Modern Methods for Data Analysis" from Monday, Jan. 11 through Friday, Jan. 15, from 10 a.m. to noon (EST). The ...