Standard Reference Data

NIST Statistical Reference Datasets - SRD 140

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Contact: William Guthrie.
Identifier: ark:/88434/mds011dkz0
Version: 1.0
The purpose of this project is to improve the accuracy of statistical software by providing reference datasets with certified computational results that enable the objective evaluation of statistical software. Currently datasets and certified values are provided for assessing the accuracy of software for univariate statistics, linear regression, nonlinear regression, and analysis of variance. The collection includes both generated and 'real-world' data of varying levels of difficulty. Generated datasets are designed to challenge specific computations. These include the classic Wampler datasets for testing linear regression algorithms and the Simon & Lesage datasets for testing analysis of variance algorithms. Real-world data include challenging datasets such as the Longley data for linear regression, and more benign datasets such as the Daniel & Wood data for nonlinear regression. Certified values are 'best-available' solutions. The certification procedure is described in the web pages for each statistical method. Datasets are ordered by level of difficulty (lower, average, and higher). Strictly speaking the level of difficulty of a dataset depends on the algorithm. These levels are merely provided as rough guidance for the user. Producing correct results on all datasets of higher difficulty does not imply that your software will pass all datasets of average or even lower difficulty. Similarly, producing correct results for all datasets in this collection does not imply that your software will do the same for your particular dataset. It will, however, provide some degree of assurance, in the sense that your package provides correct results for datasets known to yield incorrect results for some software. The Statistical Reference Datasets is also supported by the Standard Reference Data Program.
Research Areas
NIST R&D: Standards: Reference data
Keywords: ANOVAsBayes theoremsBayesianBayesian computationsBayesian statisticsShow more...
These data are public.
For more information, please visit the home page.
Data and related material can be found at the following locations:
Version: 1.0
Cite this dataset
William Guthrie (2003), NIST Statistical Reference Datasets - SRD 140, National Institute of Standards and Technology, http://www.itl.nist.gov/div898/strd/index.html (Accessed 2025-04-24)
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NERDm
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