This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...

Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly driving discovery. At The University of Texas at Arlington, data scientists ...

Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical system.

Applied statistics is crucial for transforming quantitative data into actionable insights, enabling informed decision-making for working professionals and advancing research across disciplines. The ...