Statistics
Can you apply?
This grant is for research organizations and academic institutions seeking support for statistical science research and methodology development.
Eligible applicants typically include universities, colleges, research institutions, and nonprofit research organizations with strong research capacity. Researchers from mathematics, statistics, computer science, and related disciplines can apply as principal investigators. U.S. citizenship or permanent residency is required for principal investigators.
The program supports fundamental research in statistical theory, methods, and applications. Funded activities include basic research projects, curriculum development in statistics, and workforce training. Research must advance the field of statistics or enable other scientific disciplines.
Grant funding typically supports single research projects or multi-investigator teams. Applications from underrepresented groups and early-career researchers are encouraged.
Program description
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.
Who can apply
Eligible applicants
How to apply
Application links
Required documents
- Project Narrative
- Budget and Budget Justification
- Biographical Sketches (NSF format)
- Current and Pending Support
- Letters of Support
- Facilities and Resources documentation
Program contact
- 👤 U.S. National Science Foundation
- 📧 grantsgovsupport@nsf.gov
- 📞 703-292-4203
Funding track record
Recent awards under CFDA 47.049 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
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$570,618,065
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$480,514,346
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$406,246,554
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$277,033,094
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$236,459,999
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$190,969,692
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$159,846,534
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$144,261,921
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$140,880,752
-
$124,000,000
Top States by Funding
- VA 5 awards $955.1M
- DC 4 awards $907.5M
- CA 12 awards $589.6M
- AZ 8 awards $566.5M
- NY 7 awards $319.1M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 47.049). How funding has trended year over year.
| 2024 | $1,539,910,000 | |
| 2025 | $1,537,650,000 | |
| 2026 est. | $512,280,000 |
FAQ
Who can be the Principal Investigator on a Statistics grant?
Faculty members, senior researchers, and postdoctoral fellows at eligible institutions. PIs must be U.S. citizens or permanent residents.
What types of research does NSF Statistics support?
Fundamental statistics research, statistical methodology, and applications to other sciences. Proposals should advance statistical theory or practice.
Are there budget limits for this grant?
Typical grants range widely by project scope. Check the solicitation for specific cap limits and allowed indirect costs.
How competitive is this program?
Very competitive. NSF Statistics receives hundreds of proposals annually with typical funding rates around 20-25%.
Can international collaborators be included?
Yes, but the lead institution and PI must be U.S.-based. Foreign collaborators should be clearly justified.
💡 Tips for applicants
- Align your research directly to NSF Statistical Science priorities. Review recent awards to identify current focus areas.
- Demonstrate both intellectual merit and broader impacts clearly and separately in your proposal.
- Include preliminary data or results showing feasibility of your proposed methods or theory.
- Strengthen applications with letters of support from collaborators or industry partners who will use your research.
- Submit early and have senior colleagues review your proposal before final submission.
⚠️ Common mistakes
Proposals that lack clear intellectual merit or fail to explain why the research matters to statistics as a field. Broader impact sections that sound generic or disconnected from the actual research.
Budgets that seem inflated relative to the proposed work or don't include sufficient detail. Proposals that read as incremental improvements rather than advancing statistical science.
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