Bayesian factor analysis offers a probabilistic framework for uncovering latent structure in datasets where the number of observed variables greatly exceeds the sample size. By positing that ...

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 ...

An international research team led by scientists from Osaka Metropolitan University has developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. This ...

New FDA guidance on the use of Bayesian statistics signals a broader shift in accommodating more flexible clinical trial ...

The "replication crisis" refers to a problem in the sciences where findings from previous experiments don't hold up when studies are repeated. It is a particular issue for those in the behavioral ...

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 ...

Randomized controlled trials are considered the golden standard for estimating treatment effect but are costly to perform and not always possible. Observational data, although readily available, is ...