The National Academies Committee on Applied and Theoretical Statistics has released proceedings from its June 2016 workshop titled “Refining the Concept of Scientific Inference When Working with Big Data,” co-chaired by Alfred Hero, MIDAS co-director and the John H Holland Distinguished University Professor of Electrical Engineering and Computer Science.
The report can be downloaded from the National Academies website.
The workshop explored four key issues in scientific inference:
- Inference about causal discoveries driven by large observational data
- Inference about discoveries from data on large networks
- Inference about discoveries based on integration of diverse datasets
- Inference when regularization is used to simplify fitting of high-dimensional models.
The workshop brought together statisticians, data scientists and domain researchers from different biomedical disciplines in order to identify new methodological developments that hold significant promise, and to highlight potential research areas for the future. It was partially funded by the National Institutes of Health Big Data to Knowledge Program, and the National Science Foundation Division of Mathematical Sciences.