www niss org Overview The National Institute of

  • Slides: 5
Download presentation

www. niss. org Overview The National Institute of Statistical Sciences (NISS) is an independent

www. niss. org Overview The National Institute of Statistical Sciences (NISS) is an independent research organization that serves as a neutral, objective expert in delivering research in science and public policy to its affiliates in academia, industry and government. NISS identifies, catalyzes and fosters high-impact crossdisciplinary and cross-sector research involving the statistical and data sciences.

www. niss. org The NISS Affiliate Program Brings together statistical, mathematical and data science

www. niss. org The NISS Affiliate Program Brings together statistical, mathematical and data science professionals from all sectors – academia, industry, government / national labs – to support research, information dissemination, human resource development and networking. Affiliates take advantage of events NISS has in the pipeline or work to define new opportunities that will address their needs, and likely the needs of NISS colleagues as well.

www. niss. org People James L. Rosenberger (Director), Nell Sedransk (Director-DC) Mary Batcher (Board

www. niss. org People James L. Rosenberger (Director), Nell Sedransk (Director-DC) Mary Batcher (Board of Trustees Chair), Raymond Bain (Vice Chair), Christy Chuang-Stein (Affiliates Cmte Chair) Board of Trustees James Booth (Cornell U) Kate Crespi (UCLA) Jan Hannig (UNC) Nicholas Jewell (UC Berkeley), Mimi Kim (Einstein) Dennis Lin (PSU) Bhramar Mukherjee (U Michigan) Jerry Reiter (Duke U) Hal Stern (UC Irvine) Ron Wasserstein (ASA) Alyson Wilson (NCSU) Sam Woolford (Bentley U) Tim Hesterberg (Google) Leland Wilkinson (H 2 O) Gabriel Huerta (Sandia) Phil Kott (RTI) Tommy Wright (Census)

www. niss. org Motivation – 1990 IMS Report Domain knowledge and statistical theory and

www. niss. org Motivation – 1990 IMS Report Domain knowledge and statistical theory and methods are inseparable. The continued health of statistics depends strongly on continuing cross -disciplinary research in many fields. Close collaborations among statisticians and scientists push forward the frontiers. Constrained resources and existing infrastructure within academia, government and industry thwart growth and development of the needed cross-disciplinary (and cross-sector) research.