I thought that the following might be of interest to other ASA members:
The videos from the "Refining the Concept of Scientific Inference When Working with Big Data" workshop which took place on June 8-9, 2016 at the National Academies of Sciences, Engineering, and Medicine in Washington, D.C. are now available for viewing at:
http://sites.nationalacademies.org/DEPS/BMSA/DEPS_171738
The Committee on Applied and Theoretical Statistics held a two-day workshop on the challenges of applying scientific inference to big data. The workshop brought 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 was to identify new developments that hold significant promise and to highlight potential research program areas for the future.
Kudos to CATS for organizing this useful workshop and making the materials and videos available to the community,
Nick
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Nicholas Horton
Chair, Section on Statistics Education
Professor of Statistics
Amherst College
Amherst, MA United States
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