Apply to PD 08-1269 as follows:
For full proposals submitted via FastLane:
standard Grant Proposal Guide proposal preparation guidelines apply.
For full proposals submitted via Grants.gov:
the NSF Grants.gov Application Guide; A Guide for the Preparation and Submission of NSF Applications
via Grants.gov Guidelines applies.
(Note: The NSF Grants.gov Application Guide is available on the Grants.gov website and on the
NSF website at: http://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide)
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 16-1), is
effective for proposals submitted, or due, on or after January 25, 2016. Please be advised that, depending
on the specified due date, the guidelines contained in NSF 16-1 may apply to proposals submitted in response to this
Full Proposal Window: October 23, 2016
November 7, 2016
October 23 - November 7, Annually Thereafter
The statistics program has a submission window in from October 23 to November 7. Proposals submitted after 5pm (local time) on November 7 will be returned without review. Conference and workshop proposals should be submitted eight months before the requested starting date.
The Statistics Program supports research in statistical theory and methods, including research in statistical methods for applications to any domain of science and engineering. The theory forms the base for statistical science. The methods are used for stochastic modeling, and the collection, analysis and interpretation of data. The methods characterize uncertainty in the data and facilitate advancement in science and engineering. The Program encourages proposals ranging from single-investigator projects to interdisciplinary team projects.
Conferences and Workshops in the Mathematical Sciences
Focused Research Groups in the Mathematical Sciences
Algorithms for Threat Detection
Joint DMS/NIGMS Initiative to Support Research at the Interface of the Biological and Mathematical Sciences
Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences
Mathematical Sciences Postdoctoral Research Fellowships
Faculty Early Career Development (CAREER) Program
Collaborative Research in Computational Neuroscience
Critical Techniques, Technologies and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering
THIS PROGRAM IS PART OF
Disciplinary Research Programs
What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)
Map of Recent Awards Made Through This Program