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Summary
Summary
An essential reference for statisticians, engineers, and quality professionals in industry, academia, and government, Encyclopedia of Statistics in Quality and Reliability offers an essential knowledge source in an area where one is sorely needed. Providing a practical orientation with a large selection of case studies, this multi-volume state-of-the-art publication examines the widespread use of Six Sigma. This popular quality measuring technique is a highly adaptable tool with many wide-reaching applications in a large variety of sectors.
Author Notes
Editors-in-Chief
Fabrizio Ruggeri, CNR-IMATI, Milan, ItalyProf. Ruggeri''s research interests include reliability, general statistical modelling with applications in industry, and Bayesian statistics. He is a former President of the European Network for Business and Industrial Statistics (ENBIS) and former Board member of the International Society for Bayesian Analysis (ISBA). He edited two volumes on Bayesian Robustness and special issues of journals. He also served as the Editor (1999-2002) of the ISBA Bulletin and is currently Editor-in-Chief of Applied Stochastic Models in Business and Industry and an Editor of Bayesian Analysis. He is Co-Director of the Applied Bayesian Statistics summer school (ABS) and Chair of the Scientific Committee of the Bayesian Inference in Stochastic Processes (BISP) series of workshops. He is a faculty in the Ph.D. programme in Mathematics and Statisics at the University of Pavia and the Master programme in Applied Mathematics for Industry at University of Milano Bicocca. He has been member of many committees, including Savage Award, De Groot Award and Box Medal. He is the author of nearly 100 publications.
Ron S. Kenett, KPA Ltd, Raanana, Israel and University of Turin, Turin, Italy. Professor Kenett''s interests include Strategic Planning and Quality Management, Industrial Statistics and Biostatistics, Statistical Process Control and Design of Experiments, Survey Methodology and Software Quality. He is a Fellow of the Royal Statistical Society, a Senior Member of the American Society for Quality,past member of the board of the Israeli Statistical Association and past president of ENBIS, the European Network for Business and Industrial Statistics. He is editor in chief of the journal Quality Technology and Quantitative Management and associate editor of the Journal of the Royal Statistical Society (A) and Applied Stochastic Models in Business and Industry. He is co author of 4 books and over 130 papers, including Modern Industrial Statistics (with S. Zacks), Duxbury Press 1998, and Software Process Quality - Management and Control (with E. Baker) Marcel Dekker Inc., 1999. Ron has been a consultant for leading corporations such as AT&T, hp, EDS, SanDisk, IBM and Amdocs. His career has combined academic positions with activity in the industrial and business sector.
Frederick W. Faltin , The Faltin Group, Cody, WY, USAMr. Faltin''s interests include Managing Six Sigma, Design for Six Sigma, Business Process Simulation & Optimization, Financial Quality, Supply Chain Management, and Design of Experiments. He is a Fellow of the American Statistical Association, a recipient of the Shewell Prize of the American Society for Quality, and has served on the selection committees of various ASQ awards. He served on the Editorial Review Board of the Journal of Quality Technology, is a past Chair of ASA''s Quality and Productivity Section, and is a member of the boards of the Quality & Productivity Research Conference and the Fall Technical Conference. Mr. Faltin has published dozens of papers on applications of mathematics & statistics, and has authored Six Sigma curricula for a number of prominent companies, including Motorola--the company that invented Six Sigma. He was formerly manager of the Strategic Enterprise Technologies laboratory at GE''s Global Research Center, and is today Managing Director of The Faltin Group, which he founded in 1999.
Editors
Basics Statistics
Jeroen de Mast , University of Amsterdam,
The Netherlands
Computationally Intensive Methods & Simulation
Simon Wilson , Trinity College Dublin, Ireland
Design of Experiments & Robust Design
David Steinberg , Tel Aviv University, Israel
Health, Safety & Environmental Applications
Tony Greenfield , Greenfield Research, UK
Management of Quality & Business Statistics
Blanton Godfrey , College of Textiles, USA
Ramon Leon , University of Tennessee, USA
Process Capability & Measurement Systems Analysis
Connie Borror , University of Illinois, USA
Process Control
Mike Adams , University of Alabama, USA
Reliability: Life Cycle & Warranty Cost Prediction
Refik Soyer , George Washington University, USA
Reliability: Life Distribution Modeling & Accelerated Testing
Tom Mazzuchi , George Washington University, USA
Sampling
Rainer Göb , University of Wuerzberg, Germany
Statistical and Stochastic Modelling
Shelley Zacks , Binghamton University, USA
System Reliability
Steven Rigdon , Southern Illinois University, USA
Reviews 1
Choice Review
In today's world one depends on the quality of consumer products purchased without giving much thought to how these products are quality tested. The Encyclopedia of Statistics in Quality and Reliability presents explanatory articles on the various statistical tests and procedures used in these fields. The editors have done a good job of gathering together in one place comprehensible articles on these important areas of knowledge for those working in science, government, and industry. Included are current bibliographical references to further information on each subject. A large group of knowledgeable scholars have written over 400 excellent articles, accompanied by good illustrations where applicable. However, libraries that already own the second edition of the more comprehensive Encyclopedia of Statistical Sciences, ed. by S. Kotz (CH, Jul'06, 43-6253) should find it sufficient. Although the authors of the two works generally are different, many of the subjects in this new encyclopedia are also covered in the larger one. This excellent new publication is only necessary for those library collections specializing in quality and reliability testing, or for libraries that could not afford the previous encyclopedia but need information on statistical testing. Summing Up: Recommended. Lower-level undergraduates and above; general readers. J. O. Christensen Brigham Young University
Table of Contents
| Entries in the published Encyclopedia are presented in alphabetic order |
| The following listing shows articles grouped under the section headings used for editorial planning of the work |
| Basic Statistics |
| Assignable cause |
| Autocorrelation function |
| Bias of an estimator |
| Box and Cox transformation |
| Coefficient of determination (R2) |
| Collinearity |
| Confidence intervals |
| Correlation |
| Covariance |
| Covariate |
| Cumulative distribution function (CDF) |
| Data collection |
| Degrees of freedom |
| Dependence |
| Descriptive Statistics |
| Estimation |
| Expectation |
| Exploratory data analysis |
| Exponentially weighted moving average (EWMA) |
| Graphical representation of data |
| Heteroscedasticity |
| Homogeneity of Variances; Homoscedasticity |
| Hotelling's T2 |
| Hypothesis testing |
| Kurtosis |
| Lack of fit |
| Laws of large numbers |
| Least squares estimation |
| Leverage |
| Maximum likelihood |
| Mean square error |
| Measures of Association |
| Measures of Location |
| Measures of Scale |
| Missing data and imputation |
| Moments |
| Monte Carlo methods |
| Moving averages |
| Multi-vari chart |
| Multivariate analysis |
| Nonparametric Tests |
| Normal distribution |
| Normality Tests |
| Observational studies |
| Outliers |
| Overview of Statistics |
| Parametric tests |
| Pareto chart |
| Pooled variance, pooled estimate |
| Power |
| Probability density function (PDF) |
| Probability density functions |
| Probability plots |
| Probability theory |
| P-values |
| Quantiles |
| Quartiles |
| Residuals |
| Runs, runs tests |
| Sample Size Determination |
| Sigma Metric |
| Significance level |
| Six Sigma Method |
| Skewness |
| Standard error |
| Statistical Methods for Counts, Rates and Proportions |
| Sum of squares |
| Time series analysis |
| Transfer function |
| Trimmed mean |
| Variables |
| Variance |
| Variance components |
| Computationally Intensive Methods & Simulation |
| Asymptotic Reliability Analysis of Very Large Systems |
| Bayesian networks in reliability |
| Bayesian robustness: theory and computation |
| Bootstrap And Jacknife: Overview |
| Classification and Regression Tree Methods |
| Computational Issues in Network Reliability |
| Convergence and Mixing in Markov Chain Monte Carlo |
| Data Mining in Quality and Reliability |
| Decision search via simulation |
| Density and failure rate estimation |
| Dirichlet process, Simulation of |
| Discrete event simulation for reliability prediction |
| Dynamic Programming |
| Methods in Repair and Replacement |
| Evaluation techniques in data mining |
| Expectation Maximisation Algorithm |
| Failure Modes and Effects Analysis, Implementation of |
| Fault tree analysis for large systems |
| Integrating computer and physical experiment data |
| Laplace approximations in Bayesian lifetime analysis |
| Levy Processes, Simulation of |
| Life Distributions, Simulation of |
| Lifetime Distributions, Optimization Methods for |
| Markov chain Monte Carlo, Introduction |
| Monte Carlo Methods: Univariate and Multivariate |
| Neural networks in Statistical Process Control |
| Optimal Reliability Design- Algorithms and Comparisons |
| Optimal Reliability Design- ModellingP |
