Selection of a tightened-normal-tightened system for given values of the acceptable quality level and limiting quality level

A table and a procedure are given to find the tightened-normal-tightened system involving the minimum sum of producer's and consumer's risks for a specified acceptable quality level and limiting quality level.     

企业数据质量的评价与控制

如同质量是产品的生命一样 ,数据的准确性可以说是统计工作的生命。就政府统计而言 ,中国的统计数据内容广泛 ,有着其他国家无与伦比的丰富性 ;但是 ,我国统计数据的总体质量不高也是一个无法回避的问题。其中 ,数据审核体系的缺陷、统计方法的随意性和人为因素对数据质量的影响不容忽视。目前 ,企业数据直接上报的数据收集方式正在逐步推广 ,数据质量在报送环节上的控制因素在减少 ,而大范围的超级汇总常常掩盖分企业的数据错误。在这种情况下 ,进行数据的深层次开发和研究将面临一些意想不到的困难。在进行统计分析时 ,我们曾发现人均产值…     

Multivariate quality control

This paper includes both the motivation for multivariate quality control, and a discussion of some ot rhe techniques currently available. The emphasis focuses primarily on control charts and includes the T² -chart, the use of principal components anm some recent developments, multivariate analogs of CUSUM cnarts and the use of the Andrews procedure. Some of the problems associated with multivariate acceptance sampling are presented, and the paper concludes with some recommendauons for future researcn and development.     

Synthesis and quality

By combining a keen interest in agriculture and natural science with his ability as a mathematician, John Nelder has enjoyed a long and distinguished career as an agricultural statistician. In conversation with Helen Joyce, he offers a personal view of the world of statistics and his own contributions to it.     

Agricultural data quality

Since the late 19th century, the Agricultural Census has been an important source of data on land use and numbers of livestock and farm workers. It works well as a general source of large area results, but in late 2003, in response to customer demand to make data available at smaller geographical scales, the Welsh Assembly released a spreadsheet of results at the small area level from the 2002 Agricultural Census. In this case study, Stuart Neil discusses the issues of data quality that arose in compiling these data.     

Modified tables for the selection of quick switching systems for values of the given acceptable quality level and limiting quality level

The paper presents modified tables derived from the work of Romboski and Soundararajan & Arumainayagam for the selection of quick switching systems of type QSS-2, QSS-3 and QSS-4 for given values of acceptable quality level, limiting quality level, producer's risk and consumer's risk. The plans selected from the tables will involve a smaller average sample number at the acceptable quality level.     

Nonparametric quality control charts based on the sign statistic

Nonparametric control chart are presented for the problem of detecting changes in the process median (or mean), or changes in the process variability when samples are taken at regular time intervals. The proposed procedures are based on sign-test statistics computed for each sample, and are used in Shewhart and cumulative sum control charts. When the process is in control the run length distributions for the proposed nonparametric control charts do not depend on the distribution of the observations. An additional advantage of the non-parametric control charts is that the variance of the process does not need to be established in order to set up a control chart for the mean. Comparisons with the corresponding parametric control charts are presented. It is also shown that curtailed sampling plans can considerably reduce the expected number of observations used in the Shewhart control schemes based on the sign statistic.     

International quality system standards

Quality, which embraces the fitness of aproduct (orservice) to satisfy customer requirements is of tena major consideration in purchasing decisions.

Recognized national and international product standards which reflect the require ment of world markets, and not just the particular conditions of the domestic market can helpreduce the multiplicity of procurements pecification ,increase product volumes ,reduceunit costs and promote consistent product qua1ity. Consistentcompliance with thesest and ardscan be ensured through the use of quality assurance systems.     

Cusum quality control-multivariate approach

A new multivariate approach to quality control is presented. On the basis of sequential probability ratio tests, a multivariate cumulative sum chart is derived. Using an approximation to the noncentral x² distribution, a linear decision rule is obtained.     

Statistical and quality control standards in the U.S

The U.S. standards system is a system of voluntary consensus standards in the private sector. There are more than 750 orgainzations in the U.S. that issue standards. Two very important standards orgainzations are ASTM Committee E-11 on Statistical Methods and ANSI Committee Z-1 on Quality Assurance develop statistical standards, and standards under the jurisdiction of these committees are listed. The most widely-used statistical standards are the standard tables for sampling inspection, which were developed by the U. S. militart, and have been adopted, modifed or revised to appear in various standard systems, both military and civilian, national and international     

Determination of variable-lot-size attribute sampling plan indexed by the acceptable quality level and average outgoing quality level for continuous production

In this paper, procedures and tables for the selection of a variable-lot-size attribute sampling plan for continuous production are given, and the advantages of this plan relative to a fixed-lot-size plan are also discussed.     

Bivariate dispersion quality control charts

A Shewhart procedure is used to simultaneously control the standard deviations of quality characteristics assumed to have a bivariate normal distribution. Following Krishnaiah et al (1963), we use the bivariate chi-square distribution to determine probabilities of out-of-control signals and thus the respective average run lengths (ARLs). Results from an example indicate that for both one-sided and two-sided cases, signals occur only slightly more quickly for changes in the process standard deviations for uncorrected variables than for correlated variables.     

Hierarchical bayes quality measurement plan

Quality Measurement Plan (QMP) as developed by Hoadley (1981) is a statistical method for analyzing discrete quality audit data which consist of the expected number of defects given the standard quality. The QMP is based on an empirical Bayes (EB) model of the audit sampling process. Despite its wide publicity, Hoadley's method has often been described as heuristic. In this paper we offer an hierarchical Bayes (HB) alternative to Hoadley's EB model, and overcome much of the criticism against this model. Gibbs sampling is used to implement the HB model proposed in this paper. Also, the convergence of the Gibbs sampler is monitored via the algorithm of Gelman and Rubin (1992).     

A statistical testing framework for evaluating the quality of measurement processes

In this paper we address the evaluation of measurement process quality. We mainly focus on the evaluation procedure, as far as it is based on the numerical outcomes for the measurement of a single physical quantity. We challenge the approach where the ‘exact’ value of the observed quantity is compared with the error interval obtained from the measurements under test and we propose a procedure where reference measurements are used as ‘gold standard’. To this purpose, we designed a specific t-test procedure, explained here. We also describe and discuss a numerical simulation experiment demonstrating the behaviour of our procedure.     

The american statistical association's response to the challenges of improving quality

The American Statistical. Association recently created a Comittee on Quality and Productivity This committee has beguna large number of activities that will bed escribed in this talk. Inaddition, the American Statistical Association hasunde taken alarge -scale project on Quantitatve Literacy that will also be described in this talk. Finally, some challenges in educating thegeneral publicin statistical reasoning will be discussed.     

On the quality of reinterview data with application to the Current Population Survey

"The [U.S.] Current Population Survey (CPS) reinterview sample consists of two subsamples: (a) a sample of CPS households is reinterviewed and the discrepancies between the reinterview responses and the original interview responses are reconciled for the purpose of obtaining more accurate responses..., and (b) a sample of CPS households, nonoverlapping with sample (a), is reinterviewed 'independently' of the original interview for the purpose of estimating simple response variance (SRV). In this article a model and estimation procedure are proposed for obtaining estimates of SRV from subsample (a) as well as the customary estimates of SRV from subsample (b).... Data from the CPS reinterview program for both subsamples (a) and (b) are analyzed both (1) to illustrate the methodology and (2) to check the validity of the CPS reinterview data. Our results indicate that data from subsample (a) are not consistent with the data from subsample (b) and provide convincing evidence that errors in subsample (a) are the source of the inconsistency."     

A standardized distance-based index to assess the quality of space-filling designs

One of the most used criterion for evaluating space-filling design in computer experiments is the minimal distance between pairs of points. The focus of this paper is to propose a normalized quality index that is based on the distribution of the minimal distance when points are drawn independently from the uniform distribution over the unit hypercube. Expressions of this index are explicitly given in terms of polynomials under any \(L_p\) distance. When the size of the design or the dimension of the space is large, approximations relying on extreme value theory are derived. Some illustrations of our index are presented on simulated data and on a real problem.     

Analytical approach for determining the cost optimum raw material quality level

In this paper, the expected cost of a raw

material quality characteristic is determined and

the cost optimum quality level is found. A series

of piecewise linear functions is used torepresent a general cost function. Examples are given in

which the distributions of quality characteristics are treated as being either

uniform or normal. The relationship between a raw

material characteristic and manufacturing cost is

assumed to be known

Determining cost optimum quality level Manitoba