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Data Gallery
Representative Collection of NIST and NIST-Like Data Sets To illustrate the Bayesian method in action, we present a representative collection of NIST and NIST-like data sets, and illustrate the effect of various expertise-driven prior distributions on the posterior distribution and on the final scientific/engineering quantity of interest.

In particular, select a data set of your choice to see how three different prior distributions:

  1. no prior information;
  2. uniform prior information; and
  3. normal prior information
may be formally and rigorously combined with the observed data to produce a more accurate final answer.
Univariate Location, Linear Calibration Michelson Speed of Light
Michelson Speed of Light
(Univariate Location Estimation)
Norris Ozone Calibration Curve
Norris Ozone Calibration
(Linear Calibration)
Errors in Variables, 2-Lab Consensus Value Guenther/ISO Nox Calibration
Guenther/ISO NOx Calibration
(Errors-in-Variables Regression)
Wise Mercury Mass Fraction
Wise Mercury Mass Fraction
(2-Lab Consensus Value)
K-Lab Consensus Value Zarr Thermal Conductivity Interlab
Zarr Thermal Conductivity
(k-Lab Consensus Value)
Schantz SRM 1946: Lake Superior Fish Tissue
Schantz SRM 1946: Lake Superior Fish Tissue (k-Lab Consensus Value)

Date created: 9/21/2001
Last updated: 9/21/2001
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