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ASTM E122-00
Standard Practice for Calculating Sample Size to Estimate, With a Specified Tolerable Error, the Average for Characteristic of a Lot or Process
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Разработчик:
Зарубежные/ASTM
ICS:
03.120.30 Application of statistical methods / Применение статистических методов
Сборник (ASTM):
14.05 Statistical Methods; Hazard Potential of Chemicals; Thermal Measurements; Manufacture of Pharmaceutical and Biopharmaceutical Products / Статистические методы; Потенциальная опасность химических веществ; Измерения теплопроводности; Производство фармацевтических изделий
Тематика:
Quality Control
Описание
Значение и использование

This practice is intended for use in determining the sample size required to estimate, with specified precision, a measure of quality of a lot or process. The practice applies when quality is expressed as either the lot average for a given property, or as the lot fraction not conforming to prescribed standards. The level of a characteristic may often be taken as an indication of the quality of a material. If so, an estimate of the average value of that characteristic or of the fraction of the observed values that do not conform to a specification for that characteristic becomes a measure of quality with respect to that characteristic. This practice is intended for use in determining the sample size required to estimate, with specified precision, such a measure of the quality of a lot or process either as an average value or as a fraction not conforming to a specified value.

Область применения

1.1 This practice covers simple methods for calculating how many units to include in a random sample in order to estimate with a prescribed precision, a measure of quality for all the units of a lot of material, or produced by a process. This practice will clearly indicate the sample size required to estimate the average value of some property or the fraction of nonconforming items produced by a production process during the time interval covered by the random sample. If the process is not in a state of statistical control, the result will not have predictive value for immediate (future) production. The practice treats the common situation where the sampling units can be considered to exhibit a single (overall) source of variability; it does not treat multi-level sources of variability.

Ключевые слова:
calculating test values; empirical knowledge; sampling; size; statistical methods