Refining the Concept of Scientific Inference When Working With Big Data
Event Information
Description
The Committee on Applied and Theoretical Statistics invites you to attend a two-day workshop on the challenges of applying scientific inference to big data. The workshop will bring together statisticians, data scientists and domain researchers from different biomedical disciplines to explore four key issues of 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 aim of the workshop is to identify new developments that hold significant promise and to highlight potential research program areas for the future. The preliminary program is now available. Please contact Michelle Schwalbe at mschwalbe@nas.edu with questions about this workshop.
This workshop will be professionally webcast. If you intend to join us online, please register as a webcast participant. A link to the webcast will be made available closer to the event.
We recommend taking public transportation, as public parking near the Keck Center is limited. The closest metro stops are Gallery Pl-Chinatown and Judiciary Square.
Organizer NASEM Math and Statistics
Organizer of Refining the Concept of Scientific Inference When Working With Big Data
The Board on Mathematical Sciences and Analytics (BMSA) of the National Academies of Sciences, Engineering, and Medicine leads activities in the mathematical sciences at the National Academies in topic areas including from applied mathematics, scientific computing, and risk analysis.
The Committee on Applied and Theoretical Statistics (CATS) of the National Academies of Sciences, Engineering, and medicine organizes studies and events focusing on the statistical sciences, big data and data science, statistical education, the use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.
