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008170727s1988    onc    |o    f|0| 0 eng d
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aCS11-617/88-27E-PDF
1001 |aMacMillan, J. H.
24512|aA non-parametric empirical Bayes approach for estimating a process average in quality control |h[electronic resource] / |cby J. H. MacMillan and W. V. Mudryk.
260 |a[Ottawa] : |bStatistics Canada, |c1988.
300 |a[14] p.
4901 |aWorking paper ; |v88-27
500 |aDigitized edition from print [produced by Statistics Canada].
500 |a"Working Paper No. BSMD-88-027E."
500 |a"August 1988."
504 |aIncludes bibliographic references.
5203 |a"At Statistics Canada, acceptance sampling is used as a method of quality control for survey processing operations. The sampling plans which are used will ensure minimum inspection at a specific incoming error level. This error level is estimated by a quantity known as the process average. It is an unknown parameter which is usually estimated from current inspection results, but frequently the estimation is difficult because of small sample sizes. Greater accuracy in the estimate may be produced by using more data from previous samples to improve upon the current sample result. A non-parametric empirical Bayes estimator of the process average is presented. An approximate confidence interval is also constructed. Examples are provided"--Abstract.
546 |aAbstract also in French.
69207|2gccst|aStatistical analysis
69207|2gccst|aMethodology
7001 |aMudryk, W. V.
7101 |aCanada. |bStatistics Canada. |bMethodology Branch.
830#0|aWorking paper (Statistics Canada. Methodology Branch)|v88-27|w(CaOODSP)9.834763
85640|qPDF|s972 KB|uhttps://publications.gc.ca/collections/collection_2017/statcan/11-613/CS11-617-88-27-eng.pdf