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Amanda Koepke (Fed)

Mathematical Statistician

Amanda Koepke (she/her/hers) graduated from Texas Tech University in 2008 with a B.A. in Mathematics and Statistics and a B.A. in Psychology. In 2014 she received her Ph.D. in Statistics from the University of Washington. She completed a year-long postdoctoral research fellowship at the Fred Hutchinson Cancer Research Center in Seattle before joining the Statistical Engineering Division at NIST in 2015.

Amanda's current research interests include Bayesian analysis, meta-analysis/interlaboratory studies, and spectral analysis. She is participating in the ITL Speakers Bureau:


Technical Areas of Research and Consulting

  • Bayesian analysis
  • Statistical modeling
  • Uncertainty analysis
  • Markov chain Monte Carlo methods
  • Consensus values



  • Symposium on Data Science & Statistics Program Chair (2024), Program Chair-Elect (2023), and Co-chair of Computational Statistics track (2022)
  • Featured in the American Statistical Association (ASA) magazine (2023):
  • Chair of ASA Government Statistics Section (GSS) Mentoring committee (2021-2024) and member of GSS Fellows committee (2021-2023)
  • Member of the CU Boulder Professional MS in Applied Mathematics Advisory Board
  • ITL Diversity Committee member


  • 2023 ITL Outstanding Technology Transfer Award
  • 2021 ITL Outstanding Contribution to Enhance Diversity Award, for contributions to an exceptional range of NIST diversity programs, including leadership in outreach and commitment to improving inclusivity.
  • NIST Recommendation for Recognition (2020), recognizing "significant contributions to gender diversity" through identifying and understanding the trends in 10 years of NIST HR data.
  • 2015 Young Investigator Award from the Statistics in Epidemiology Section of the American Statistical Association.


Decision Tree for Key Comparisons

Antonio Possolo, Amanda Koepke, David Newton, Michael R. Winchester
This contribution describes a Decision Tree intended to guide the selection of statistical models and data reduction procedures in key comparisons (KCs). The
Created June 5, 2018, Updated November 6, 2023