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4.1 In Case 1, the sample is selected from a process or a very large population of interest. The population is essentially unlimited, and each item either has or has not the defined attribute. The population (process) has an unknown fraction of items p (long run average process non-conforming) having the attribute. The sample is a group of n discrete items selected at random from the process or population under consideration, and the attribute is not exhibited in the sample. The objective is to determine an upper confidence bound, pu, for the unknown fraction p whereby one can claim that p ≤ pu with some confidence coefficient (probability) C. The binomial distribution is the sampling distribution in this case.
4.2 In Case 2, a sample of n items is selected at random from a finite lot of N items. Like Case 1, each item either has or has not the defined attribute, and the population has an unknown number, D, of items having the attribute. The sample does not exhibit the attribute. The objective is to determine an upper confidence bound, Du, for the unknown number D, whereby one can claim that D ≤ Du with some confidence coefficient (probability) C. The hypergeometric distribution is the sampling distribution in this case.
4.3 In Case 3, there is a process, but the output is a continuum, such as area (for example, a roll of paper or other material, a field of crop), volume (for example, a volume of liquid or gas), or time (for example, hours, days, quarterly, etc.) The sample size is defined as that portion of the “continuum” sampled, and the defined attribute may occur any number of times over the sampled portion. There is an unknown average rate of occurrence, λ, for the defined attribute over the sampled interval of the continuum that is of interest. The sample does not exhibit the attribute. For a roll of paper this might be blemishes per 100 ft2; for a volume of liquid, microbes per cubic litre; for a field of crop, spores per acre; for a time interval, calls per hour, customers per day or accidents per quarter. The rate, λ, is proportional to the size of the interval of interest. Thus, if λ = 12 blemishes per 100 ft2 of paper, this is equivalent to 1.2 blemishes per 10 ft2 or 30 blemishes per 250 ft2. It is important to keep in mind the size of the interval in the analysis and interpretation. The objective is to determine an upper confidence bound, λu, for the unknown occurrence rate λ, whereby one can claim that λ ≤λu with s......
校准曲线由走航监测实施单位根据实际工作需要自行确定,原则上,范围宜充分考虑与相关环境质量标准、污染物排放(控制)标准中的限值浓度(含量)水平的衔接。出于以下几项考虑,建立至少六个校准点(含零浓度点)的多点校准曲线是必要且可操作的:(1)便于走航监测实施单位控制数据质量。若使用单点或三点校准曲线,每个校准点的响应变化较大,无法保证校准曲线的代表性。且使用单点曲线,可能存在截距变化的问题。...
二、研究用样品及对照物质的要求 (一)研究用样品 研究用样品应具有代表性,所用中药材产地应覆盖品种生产拟采用中药材的道地产地或主产区,每个中药材产地的样品不少于3批,并对样品批次数量从产地环境条件、质量水平等方面的代表性进行合理评价,至少应收集15批以上中药材样品,经相关专业技术人员鉴定合格后,制成中药饮片和“标准汤剂”。其中至少有3批应达到商业规模的量,以满足备案用样品的要求。...
主要问题集中在以下几个方面:1.过程控制数据或产品结果数据不真实广州丹霞生物制药有限公司用于申报生产注册的9个批次的人血白蛋白长期稳定性考察3个月、6个月、加速试验6个月大部分铝离子实际检测结果高于《中国药典》规定的200µg/L的标准。该生物制品上市后持续稳定性考察铝离子检测结果与报告不一致,实际检测结果不符合标准,企业存在修改样品名、删除检测记录重新检测等问题。...
主要问题集中在以下几个方面:1.过程控制数据或产品结果数据不真实广州丹霞生物制药有限公司用于申报生产注册的9个批次的人血白蛋白长期稳定性考察3个月、6个月、加速试验6个月大部分铝离子实际检测结果高于《中国药典》规定的200µg/L的标准。该生物制品上市后持续稳定性考察铝离子检测结果与报告不一致,实际检测结果不符合标准,企业存在修改样品名、删除检测记录重新检测等问题。...
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