GB/T 6380-2019 English PDFUS$279.00 · In stock
Delivery: <= 3 days. True-PDF full-copy in English will be manually translated and delivered via email. GB/T 6380-2019: Statistical interpretation of data - Detection and treatment of outliers in the sample from type I extreme value distribution Status: Valid GB/T 6380: Historical versions
Basic dataStandard ID: GB/T 6380-2019 (GB/T6380-2019)Description (Translated English): Statistical interpretation of data - Detection and treatment of outliers in the sample from type I extreme value distribution Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: A41 Classification of International Standard: 03.120.30 Word Count Estimation: 14,174 Date of Issue: 2019-12-10 Date of Implementation: 2020-07-01 Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration GB/T 6380-2019: Statistical interpretation of data - Detection and treatment of outliers in the sample from type I extreme value distribution---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order. Statistical interpretation of data--Detection and treatment of outliers in the sample from type I extreme value distribution ICS 03.120.30 A41 National Standards of People's Republic of China Replaces GB/T 6380-2008 Statistical processing and interpretation of data Judgment and Treatment of Outliers of Type Ⅰ Extreme Value Distribution Samples 2019-12-10 release 2020-07-01 implementation State Administration of Market Supervision Published by the National Standardization Management Committee ContentsForeword I Introduction Ⅱ 1 Scope 1 2 Normative references 1 3 Terms, definitions and symbols 1 3.1 Terms and definitions 1 3.2 Symbol 3 4 Outlier judgment 3 4.1 Origin and Determination of Outliers 3 4.2 Upper limit of the number of detected outliers 3 4.3 Single Outlier Case 3 4.4 Multiple Outlier Cases 4 5 Outlier processing 4 5.1 Processing method 4 5.2 Processing Rule 4 5.3 Recording 4 6 Judgment rules for single outliers 4 6.1 Selection of inspection methods 4 6.2 Dixon Test 4 6.3 Irwin's Test 6 7 Judgment rules for multiple outliers 7 7.1 Inspection step 7 7.2 Multiple Outlier Test Example 7 Appendix A (Normative Appendix) Critical Values for Dixon Test Table 8 Appendix B (Normative appendix) Critical values for Owen test Table 9 References 10ForewordThis standard was drafted in accordance with the rules given in GB/T 1.1-2009. This standard replaces GB/T 6380-2008 "Statistical Processing and Interpretation of Data. Judgment and Treatment of Outliers in Type I Extreme Value Distribution Samples Management, compared with GB/T 6380-2008, the main technical content changes are as follows. --- Modified the term type I extreme value distribution (see 3.1.1, 3.1.1 of the.2008 edition); --- Modified the term type I minimum distribution (see 3.1.2, 3.1.2 of the.2008 edition); --- Modified the term outlier (see 3.1.3,.2008 version 3.1.3); --- Added definition and description of order statistics (see 3.1.8); --- Modified the rules for processing outliers (see 5.2, 5.2 of the.2008 version); --- Added explanation of Weibull distribution (type III minimum value distribution) logarithmic transformation to type I minimum value distribution and calculation of outliers Example (see 6.2.3); --- Added reference ISO 16269-4..2010 (see references). This standard is proposed and managed by the National Technical Committee for Standardization of Statistical Methods (SAC/TC21). This standard was drafted. Tianjin University, Beijing Institute of Technology Zhuhai College, Ningbo Institute of Technology. The main drafters of this standard. Ma Fengshi, Xu Qizhou, Shi Daoji, Jing Guangzhu. The previous versions of the standards replaced by this standard are. --- GB/T 6380-1986, GB/T 6380-2008.IntroductionData is required for scientific research, industrial and agricultural manufacturing, and management, and the compilation, analysis, and interpretation of these data are inseparable. Open statistical methods. Statistics is a discipline that studies the collation, analysis, and correct interpretation of digital data. People each take from different sources Get a variety of digital data, these digital data are usually chaotic, and can only be used after collation and reduction, using a comprehensive statistical method The data can be organized and arranged in an organized manner. With graphics or a few important parameters, the characteristics of a large amount of data can be expressed. This not only avoids incorrect interpretation, but also minimizes the cost of obtaining satisfactory data, which improves economic efficiency. Based on the observations of the collected samples, it can be roughly confirmed that the samples come from a certain distribution. One or more of the samples were found Observations, which are far from other observations, suggest that they may come from different populations. Whether it is the actual outlier needs statistical check Check. In the testing of outliers, special attention should be paid to which basic distribution the data comes from, assumed to be from type I extreme value distribution and assumed to be from normal Distributions are very different at the time of testing, and incorrect assumptions about the distribution will cause observations to be incorrectly classified as outliers. The national standard `` Statistical Processing and Interpretation of Data '' contains the following items. --- Determination of statistical tolerance interval (GB/T 3359); --- Estimation and confidence interval of the mean (GB/T 3360); --- Comparison of two means in the case of paired observations (GB/T 3361); --- Estimation and test of binomial distribution parameters (GB/T 4088); --- Estimation and test of Poisson distribution parameters (GB/T 4089); --- Normality test (GB/T 4882); --- Judgment and treatment of outliers in normal samples (GB/T 4883); --- Estimation and test of mean and variance of normal distribution (GB/T 4889); --- Power of normal distribution mean and variance test (GB/T 4890); --- Judgment and treatment of outliers of type Ⅰ extreme value distribution samples (GB/T 6380); --- Estimation of the parameters of the Г distribution (Pearson type III distribution) (GB/T 8055); --- Judgment and treatment of outliers of index samples (GB/T 8056). Statistical processing and interpretation of data Judgment and Treatment of Outliers of Type Ⅰ Extreme Value Distribution Samples1 ScopeThis standard specifies the upper side outliers in samples with type I extreme value distribution and the lower sides in samples with type I minimum value distribution. General principles and methods of outliers. This standard applies to samples from the type Ⅰ extreme value distribution or the type Ⅰ minimum value distribution as a whole, and the sample size is 5-50. Note 1. After transforming Y = -X, the random variable of type Ⅰ minimum distribution will obey type Ⅰ extreme value distribution, so only the type Ⅰ extreme value distribution will be checked. The method of outlier outlier. Note 2. Since the type III minimum value distribution (Weibull distribution) undergoes logarithmic transformation Z = lnX, it will obey the type I minimum value distribution. Type minimum distribution (Weibull distribution) gives a method to detect outliers on the lower side. Note 3. Type I extreme value distribution is widely used in many fields such as hydrology, meteorology, earthquakes, reliability, and finance.2 Normative referencesThe following documents are essential for the application of this document. For dated references, only the dated version applies to this article Pieces. For undated references, the latest version (including all amendments) applies to this document. GB/T 3358.1 Statistical vocabulary and symbols. Part 1. General statistical terms and terms used for probability GB/T 3358.2 Statistics Vocabulary and Symbols Part 2. Applied Statistics 3 terms, definitions and symbols 3.1 Terms and definitions The terms and definitions defined in GB/T 3358.1 and GB/T 3358.2 as well as the following terms apply to this document. 3.1.1 TypeIextremevaluedistribution Has the following distribution function F (x) = exp (-e- (xa)/b) Continuous distribution with b > 0, -∞ \u003ca\u003c∞,-∞\u003cx\u003c∞。 Note 1. When a = 0, b = 1, the probability density function curve of type I extreme value distribution is shown in Figure 1. Figure 1 Curve of probability density function ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 6380-2019_English be delivered?Answer: Upon your order, we will start to translate GB/T 6380-2019_English as soon as possible, and keep you informed of the progress. The lead time is typically 1 ~ 3 working days. The lengthier the document the longer the lead time.Question 2: Can I share the purchased PDF of GB/T 6380-2019_English with my colleagues?Answer: Yes. 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