统计方法的应用标准-分析测试百科网

ISO 3951-1:2022 变量检验的抽样程序.第1部分:单个质量特性和单个AQL的逐批检验用验收质量限（AQL）索引的单个抽样计划规范

This document specifies single sampling plans for lot-by-lot inspection under the following conditions: a) where the inspection procedure is applied to a continuing series of lots of discrete products, all supplied by one producer using one production process; b) where only a single quality characteristic, x, of these products is taken into consideration, which is measurable on a continuous scale; c) where production is under statistical control and the quality characteristic, x, is distributed according to a normal distribution or a close approximation to the normal distribution; d) where a contract or standard defines a lower specification limit, L, an upper specification limit, U, or both. An item is qualified as conforming if its measured quality characteristic, x, satisfies as appropriate one of the following inequalities: 1) x ≥ L (i.e. the lower specification limit is not violated); 2) x ≤ U (i.e. the upper specification limit is not violated); 3) x ≥ L and x ≤ U (i.e. neither the lower nor the upper specification limit is violated). Inequalities 1) and 2) are cases with a single specification limit, and 3) is a case with double specification limits. Where double specification limits apply, it is assumed in this document that conformity to both specification limits is equally important to the integrity of the product. In such cases, it is appropriate to apply a single AQL to the combined percentage of a product outside the two specification limits. This is referred to as combined control.

Sampling procedures for inspection by variables — Part 1: Specification for single sampling plans indexed by acceptance quality limit (AQL) for lot-by-lot inspection for a single quality characteristi

ICS: 03.120.30
CCS
发布: 2022-08-18
实施

ISO 10576:2022 统计方法.符合规定要求的评定指南

This document sets out guidelines for checking conformity with quantifiable characteristics using the test or measurement result and its associated measurement uncertainty. This document is applicable whenever the uncertainty may be quantified according to the principles laid down in ISO/IEC Guide-98-3 (GUM). The term uncertainty is thus a descriptor for all elements of variation in the measurement result, including uncertainty due to sampling. This document does not give rules for how to act when an inconclusive result of a conformity test has been obtained. NOTE There are not limitations on the nature of the entity subject to the requirements nor on the quantifiable characteristic. Examples of entities together with quantifiable characteristics are given in Table A.1.

Statistical methods — Guidelines for the evaluation of conformity with specified requirements

ICS: 03.120.30
CCS
发布: 2022-08-05
实施

KS Q ISO 7870-7:2022 控制图.第7部分:多元控制图

Control charts — Part 7: Multivariate control charts

ICS: 03.120.30
CCS
发布: 2022-06-27
实施

KS Q ISO 7870-7-2022 控制图.第7部分:多元控制图

Control charts — Part 7: Multivariate control charts

ICS: 03.120.30
CCS
发布: 2022-06-27
实施

DB4209/T 25-2022 医院满意度测评规范

Standards for Hospital Satisfaction Evaluation

ICS: 03.120.30
CCS: A12
发布: 2022-05-30
实施: 2022-06-30

GSO ASTM F3108:2022 膝关节重建手术临床试验和/或临床注册临床结果标准指南

1.1 This guide is intended as a resource for individuals and organizations when designing clinical trials and/or clinical registries and addresses the selection of patient-reported outcomes, safety outcomes, imaging outcomes and other topics related to knee reconstructive surgery (KRS) including: (1) knee replacement systems, (2) anterior cruciate ligament reconstruction, (3) knee meniscus implants or tissue engineered medical products (TEMPs), (4) articular cartilage implants or TEMPS, (5) peri-articular knee osteotomies, (6) peri-articular knee fractures (including distal femur, patella, and proximal tibia fractures), or other knee surgeries. 1.2 In this guide, methods to measure the efficacy, effectiveness, and safety of KRS devices through standardizing clinical outcome measures are provided for designing, reviewing, and accepting human clinical trial protocols. 1.3 This guide is intended to provide consistency in study design, review, regulatory approval, and health insurance coverage approval for knee reconstructive surgery to the health care market. 1.4 For the purpose of this guide, KRS pertains to any device or TEMP that is intended to replace, resurface, reconstruct, and/or provide fixation of the knee joint, in part or in total, as a treatment for joint disease, trauma, or dysfunction, where long-term improvement in function and pain relief without major adverse events are the desired outcomes. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use. 1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

Standard Guide for Clinical Outcomes for Clinical Trials and/or Clinical Registries for Knee Reconstructive Surgery

ICS: 03.120.30
CCS
发布: 2022-05-12
实施

ASTM D7915-22 同时识别数据集中多个异常值的广义极端学生偏差（GESD）技术应用的标准实施规程

1.1 This practice provides a step by step procedure for the application of the Generalized Extreme Studentized Deviate (GESD) Many-Outlier Procedure to simultaneously identify multiple outliers in a data set. (See Bibliography.) 1.2 This practice is applicable to a data set comprising observations that is represented on a continuous numerical scale. 1.3 This practice is applicable to a data set comprising a minimum of six observations. 1.4 This practice is applicable to a data set where the normal (Gaussian) model is reasonably adequate for the distributional representation of the observations in the data set. 1.5 The probability of false identification of outliers associated with the decision criteria set by this practice is 0.01. 1.6 It is recommended that the execution of this practice be conducted under the guidance of personnel familiar with the statistical principles and assumptions associated with the GESD technique. 1.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use. 1.8 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

Standard Practice for Application of Generalized Extreme Studentized Deviate (GESD) Technique to Simultaneously Identify Multiple Outliers in a Data Set

ICS: 03.120.30
CCS
发布: 2022-05-01
实施

ASTM D6299-22 应用统计质量保证和控制制图技术评估分析测量系统性能的标准实施规程

Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance

ICS: 03.120.30
CCS
发布: 2022-05-01
实施

ASTM D6299-22e1 应用统计质量保证和控制图表技术评估分析测量系统性能的标准实施规程

1.1 This practice covers information for the design and operation of a program to monitor and control ongoing stability and precision and bias performance of selected analytical measurement systems using a collection of generally accepted statistical quality control (SQC) procedures and tools. NOTE 1—A complete list of criteria for selecting measurement systems to which this practice should be applied and for determining the frequency at which it should be applied is beyond the scope of this practice. However, some factors to be considered include (1) frequency of use of the analytical measurement system, (2) criticality of the parameter being measured, (3) system stability and precision performance based on historical data, (4) business economics, and (5) regulatory, contractual, or test method requirements. 1.2 This practice is applicable to stable analytical measurement systems that produce results on a continuous numerical scale. 1.3 This practice is applicable to laboratory test methods. 1.4 This practice is applicable to validated process stream analyzers. 1.5 This practice is applicable to monitoring the differences between two analytical measurement systems that purport to measure the same property provided that both systems have been assessed in accordance with the statistical methodology in Practice D6708 and the appropriate bias applied. NOTE 2—For validation of univariate process stream analyzers, see also Practice D3764. NOTE 3—One or both of the analytical systems in 1.5 may be laboratory test methods or validated process stream analyzers. 1.6 This practice assumes that the normal (Gaussian) model is adequate for the description and prediction of measurement system behavior when it is in a state of statistical control. NOTE 4—For non-Gaussian processes, transformations of test results may permit proper application of these tools. Consult a statistician for further guidance and information. 1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance

ICS: 03.120.30
CCS
发布: 2022-05-01
实施

ASTM E122-17(2022) 以规定精度估算批次或过程特征平均值的计算样本量的标准实施规程

1.1 This practice covers simple methods for calculating how many units to include in a random sample in order to estimate with a specified 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. 1.2 The system of units for this standard is not specified. Dimensional quantities in the standard are presented only as illustrations of calculation methods. The examples are not binding on products or test methods treated. 1.3 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

Standard Practice for Calculating Sample Size to Estimate, With Specified Precision, the Average for a Characteristic of a Lot or Process