Bayesian statistics represents a powerful framework for data analysis that centres on Bayes’ theorem, enabling researchers to update existing beliefs with incoming evidence. By combining prior ...

Harvard University is providing seven free online courses in data science, each running for eight to nine weeks and requiring ...

If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure ...

The next generation of inference platforms must evolve to address all three layers. The goal is not only to serve models ...

This article resulted from our participation in the session on the “role of expert opinion and judgment in statistical inference” at the October 2017 ASA Symposium on Statistical Inference. We present ...

The singular value decomposition is widely used to approximate data matrices with lower rank matrices. Feng and He [Ann. Appl. Stat. 3 (2009) 1634-1654] developed tests on dimensionality of the mean ...

The most widely used statistical inference procedures were invented more than 10 years ago and are not well suited for handling state-of-the art high-resolution neuroimaging data. MRI technology ...

The AI hardware landscape continues to evolve at a breakneck speed, and memory technology is rapidly becoming a defining ...