ISO 17503:2015
ISO 17503:2015 Statistical methods of uncertainty evaluation – Guidance on evaluation of uncertainty using two-factor crossed designs
CDN $251.00
Description
ISO/TS 17503:2015 describes the estimation of uncertainties on the mean value in experiments conducted as crossed designs, and the use of variances extracted from such experiments and applied to the results of other measurements (for example, single observations).
ISO/TS 17503:2015 covers balanced two-factor designs with any number of levels. The basic designs covered include the two-way design without replication and the two-way design with replication, with one or both factors considered as random. Calculations of variance components from ANOVA tables and their use in uncertainty estimation are given. In addition, brief guidance is given on the use of restricted maximum likelihood estimates from software, and on the treatment of experiments with small numbers of missing data points.
Methods for review of the data for outliers and approximate normality are provided.
The use of data obtained from the treatment of relative observations (for example, apparent recovery in analytical chemistry) is included.
Edition
1
Published Date
2015-11-06
Status
PUBLISHED
Pages
19
Language
English
Format
Secure PDF
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Abstract
ISO/TS 17503:2015 describes the estimation of uncertainties on the mean value in experiments conducted as crossed designs, and the use of variances extracted from such experiments and applied to the results of other measurements (for example, single observations).
ISO/TS 17503:2015 covers balanced two-factor designs with any number of levels. The basic designs covered include the two-way design without replication and the two-way design with replication, with one or both factors considered as random. Calculations of variance components from ANOVA tables and their use in uncertainty estimation are given. In addition, brief guidance is given on the use of restricted maximum likelihood estimates from software, and on the treatment of experiments with small numbers of missing data points.
Methods for review of the data for outliers and approximate normality are provided.
The use of data obtained from the treatment of relative observations (for example, apparent recovery in analytical chemistry) is included.
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