{"product_id":"encyclopedia-of-statistics-in-quality-and-reliability-isbn-9780470018613","title":"Encyclopedia of Statistics in Quality and Reliability","description":"An essential reference for statisticians, engineers, and quality professionals in industry, academia, and government, \u003ci\u003eEncyclopedia of Statistics in Quality and Reliability\u003c\/i\u003e 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.Mit dem Schwerpunkt auf Six Sigma bietet dieses mehrbändige, praxisorientierte Nachschlagewerk Informationen zur Anwendung statistischer Verfahren auf den Gebieten der Qualitätssicherung und Reliability-Analyse. Mit zahlreichen detaillierten Fallstudien - unentbehrlich für Fachleute aus Industrie, akademischer Forschung und Behörden.  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.  \u003cp\u003e\u003cb\u003eBasic Statistics\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAssignable cause\u003c\/p\u003e \u003cp\u003eAutocorrelation function\u003c\/p\u003e \u003cp\u003eBias of an estimator\u003c\/p\u003e \u003cp\u003eBox and Cox transformation\u003c\/p\u003e \u003cp\u003eCoefficient of determination (R2)\u003c\/p\u003e \u003cp\u003eCollinearity\u003c\/p\u003e \u003cp\u003eConfidence intervals\u003c\/p\u003e \u003cp\u003eCorrelation\u003c\/p\u003e \u003cp\u003eCovariance\u003c\/p\u003e \u003cp\u003eCovariate\u003c\/p\u003e \u003cp\u003eCumulative distribution function (CDF)\u003c\/p\u003e \u003cp\u003eData collection\u003c\/p\u003e \u003cp\u003eDegrees of freedom\u003c\/p\u003e \u003cp\u003eDependence\u003c\/p\u003e \u003cp\u003eDescriptive Statistics\u003c\/p\u003e \u003cp\u003eEstimation\u003c\/p\u003e \u003cp\u003eExpectation\u003c\/p\u003e \u003cp\u003eExploratory data analysis\u003c\/p\u003e \u003cp\u003eExponentially weighted moving average (EWMA)\u003c\/p\u003e \u003cp\u003eGraphical representation of data\u003c\/p\u003e \u003cp\u003eHeteroscedasticity\u003c\/p\u003e \u003cp\u003eHomogeneity of Variances; Homoscedasticity\u003c\/p\u003e \u003cp\u003eHotelling’s T2\u003c\/p\u003e \u003cp\u003eHypothesis testing\u003c\/p\u003e \u003cp\u003eKurtosis\u003c\/p\u003e \u003cp\u003eLack of fit\u003c\/p\u003e \u003cp\u003eLaws of large numbers\u003c\/p\u003e \u003cp\u003eLeast squares estimation\u003c\/p\u003e \u003cp\u003eLeverage\u003c\/p\u003e \u003cp\u003eMaximum likelihood\u003c\/p\u003e \u003cp\u003eMean square error\u003c\/p\u003e \u003cp\u003eMeasures of Association\u003c\/p\u003e \u003cp\u003eMeasures of Location\u003c\/p\u003e \u003cp\u003eMeasures of Scale\u003c\/p\u003e \u003cp\u003eMissing data and imputation\u003c\/p\u003e \u003cp\u003eMoments\u003c\/p\u003e \u003cp\u003eMonte Carlo methods\u003c\/p\u003e \u003cp\u003eMoving averages\u003c\/p\u003e \u003cp\u003eMulti-vari chart\u003c\/p\u003e \u003cp\u003eMultivariate analysis\u003c\/p\u003e \u003cp\u003eNonparametric Tests\u003c\/p\u003e \u003cp\u003eNormal distribution\u003c\/p\u003e \u003cp\u003eNormality Tests\u003c\/p\u003e \u003cp\u003eObservational studies\u003c\/p\u003e \u003cp\u003eOutliers\u003c\/p\u003e \u003cp\u003eOverview of Statistics\u003c\/p\u003e \u003cp\u003eParametric tests\u003c\/p\u003e \u003cp\u003ePareto chart\u003c\/p\u003e \u003cp\u003ePooled variance, pooled estimate\u003c\/p\u003e \u003cp\u003ePower\u003c\/p\u003e \u003cp\u003eProbability density function (PDF)\u003c\/p\u003e \u003cp\u003eProbability density functions\u003c\/p\u003e \u003cp\u003eProbability plots\u003c\/p\u003e \u003cp\u003eProbability theory\u003c\/p\u003e \u003cp\u003eP-values\u003c\/p\u003e \u003cp\u003eQuantiles\u003c\/p\u003e \u003cp\u003eQuartiles\u003c\/p\u003e \u003cp\u003eResiduals\u003c\/p\u003e \u003cp\u003eRuns, runs tests\u003c\/p\u003e \u003cp\u003eSample Size Determination\u003c\/p\u003e \u003cp\u003eSigma Metric\u003c\/p\u003e \u003cp\u003eSignificance level\u003c\/p\u003e \u003cp\u003eSix Sigma Method\u003c\/p\u003e \u003cp\u003eSkewness\u003c\/p\u003e \u003cp\u003eStandard error\u003c\/p\u003e \u003cp\u003eStatistical Methods for Counts, Rates and Proportions\u003c\/p\u003e \u003cp\u003eSum of squares\u003c\/p\u003e \u003cp\u003eTime series analysis\u003c\/p\u003e \u003cp\u003eTransfer function\u003c\/p\u003e \u003cp\u003eTrimmed mean\u003c\/p\u003e \u003cp\u003eVariables\u003c\/p\u003e \u003cp\u003eVariance\u003c\/p\u003e \u003cp\u003eVariance components\u003c\/p\u003e \u003cp\u003e\u003cb\u003eComputationally Intensive Methods \u0026amp; Simulation\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAsymptotic  Reliability Analysis of Very Large Systems\u003c\/p\u003e \u003cp\u003eBayesian networks in reliability\u003c\/p\u003e \u003cp\u003eBayesian robustness: theory and computation\u003c\/p\u003e \u003cp\u003eBootstrap And Jacknife: Overview\u003c\/p\u003e \u003cp\u003eClassification and Regression Tree Methods\u003c\/p\u003e \u003cp\u003eComputational Issues in Network Reliability\u003c\/p\u003e \u003cp\u003eConvergence and Mixing in Markov Chain Monte Carlo\u003c\/p\u003e \u003cp\u003eData Mining in Quality and Reliability\u003c\/p\u003e \u003cp\u003edecision search via simulation\u003c\/p\u003e \u003cp\u003eDensity and failure rate estimation\u003c\/p\u003e \u003cp\u003eDirichlet process, Simulation of\u003c\/p\u003e \u003cp\u003eDiscrete event simulation for reliability prediction\u003c\/p\u003e \u003cp\u003eDynamic ProgrammingMethods in Repair and Replacement\u003c\/p\u003e \u003cp\u003eEvaluation techniques in data mining\u003c\/p\u003e \u003cp\u003eExpectation Maximisation Algorithm\u003c\/p\u003e \u003cp\u003eFailure Modes and Effects Analysis, Implementation of\u003c\/p\u003e \u003cp\u003eFault tree analysis for large systems\u003c\/p\u003e \u003cp\u003eIntegrating computer and physical experiment data\u003c\/p\u003e \u003cp\u003eLaplace approximations in Bayesian lifetime analysis\u003c\/p\u003e \u003cp\u003eLevy Processes, Simulation of\u003c\/p\u003e \u003cp\u003eLife Distributions, Simulation of\u003c\/p\u003e \u003cp\u003eLifetime Distributions, Optimization Methods for\u003c\/p\u003e \u003cp\u003eMarkov chain Monte Carlo, Introduction\u003c\/p\u003e \u003cp\u003eMonte Carlo Methods: Univariate and Multivariate\u003c\/p\u003e \u003cp\u003eNeural networks in Statistical Process Control\u003c\/p\u003e \u003cp\u003eOptimal Reliability Design- Algorithms and Comparisons\u003c\/p\u003e \u003cp\u003eOptimal Reliability Design- Modelling\u003c\/p\u003e \u003cp\u003ePerfect Sampling\u003c\/p\u003e \u003cp\u003ePolya Trees and Their Use in Reliability and Survival Analysis\u003c\/p\u003e \u003cp\u003equality control, Computing in\u003c\/p\u003e \u003cp\u003equandrature and numerical integration\u003c\/p\u003e \u003cp\u003eResampling for lifetime distributions\u003c\/p\u003e \u003cp\u003eSimulation of the beta-Stacy process\u003c\/p\u003e \u003cp\u003eSmoothed Function Estimation for Censored Data\u003c\/p\u003e \u003cp\u003eSplines and other meta-models in reliability analysis\u003c\/p\u003e \u003cp\u003eSurvival Analysis , Nonparametric\u003c\/p\u003e \u003cp\u003e\u003cb\u003eDesign of Experiments \u0026amp; Robust Design\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAliasing in Fractional Designs\u003c\/p\u003e \u003cp\u003eAnalysis of Variance\u003c\/p\u003e \u003cp\u003eAssessment of Experimental Designs\u003c\/p\u003e \u003cp\u003eBergman-Hynen Method for Dispersion Effects\u003c\/p\u003e \u003cp\u003eBlocking\u003c\/p\u003e \u003cp\u003eBox-Behnken Designs\u003c\/p\u003e \u003cp\u003eBox-Meyer Method for Dispersion Effects\u003c\/p\u003e \u003cp\u003eCenter Points\u003c\/p\u003e \u003cp\u003eCentral Composite Designs\u003c\/p\u003e \u003cp\u003eComputer Experiments\u003c\/p\u003e \u003cp\u003eDispersion Effects\u003c\/p\u003e \u003cp\u003eFactorial Designs, Resolution of\u003c\/p\u003e \u003cp\u003eFactorial Experiments\u003c\/p\u003e \u003cp\u003eFoldover Designs\u003c\/p\u003e \u003cp\u003eFractional Factorial Designs\u003c\/p\u003e \u003cp\u003eGauge Repeatability and Reproducibility (R\u0026amp;R) Studies\u003c\/p\u003e \u003cp\u003eGeneralized Linear Models\u003c\/p\u003e \u003cp\u003eHalf-normal Plot\u003c\/p\u003e \u003cp\u003eHarvey's Method for Dispersion Effects\u003c\/p\u003e \u003cp\u003eIncomplete Block Designs\u003c\/p\u003e \u003cp\u003eInteractions\u003c\/p\u003e \u003cp\u003eLatin Hypercube Designs\u003c\/p\u003e \u003cp\u003eLatin Squares and Related Experimental Designs\u003c\/p\u003e \u003cp\u003eLenth's Method for the Analysis of Unreplicated Experiments\u003c\/p\u003e \u003cp\u003eMain Effect Designs\u003c\/p\u003e \u003cp\u003eMain Effects\u003c\/p\u003e \u003cp\u003eMinimum Aberration\u003c\/p\u003e \u003cp\u003eMixture Experiments\u003c\/p\u003e \u003cp\u003eOptimal Design\u003c\/p\u003e \u003cp\u003eOrthogonal Arrays\u003c\/p\u003e \u003cp\u003ePerformance Measures for Robust Design\u003c\/p\u003e \u003cp\u003ePlackett- Burman Designs\u003c\/p\u003e \u003cp\u003eProduct Array Designs\u003c\/p\u003e \u003cp\u003eProjectivity in Experimental Designs\u003c\/p\u003e \u003cp\u003eRandomization in Experimental Designs\u003c\/p\u003e \u003cp\u003eResponse Surface Methodology\u003c\/p\u003e \u003cp\u003eRidge Analysis in Experimental Design\u003c\/p\u003e \u003cp\u003eRobust Design\u003c\/p\u003e \u003cp\u003eRotatable Designs and Rotatability\u003c\/p\u003e \u003cp\u003eSample-Size Determination in Experimental Designs\u003c\/p\u003e \u003cp\u003eScreening Designs\u003c\/p\u003e \u003cp\u003eSequential Experimentation\u003c\/p\u003e \u003cp\u003eSignal Response Systems\u003c\/p\u003e \u003cp\u003eSignal-to-Noise Ratios for Robust Design\u003c\/p\u003e \u003cp\u003eSplit-Plot Designs\u003c\/p\u003e \u003cp\u003eSupersaturated Designs\u003c\/p\u003e \u003cp\u003eTolerance Design\u003c\/p\u003e \u003cp\u003eUniform Experimental Designs\u003c\/p\u003e \u003cp\u003e\u003cb\u003eHealth, Safety \u0026amp; Environmental Applications\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBias in Modeling and Monitoring Health Outcomes\u003c\/p\u003e \u003cp\u003eCase Series Analysis, Vaccine Safety Evaluation Using a Suitable Motivating Example.\u003c\/p\u003e \u003cp\u003eCase-control Studies\u003c\/p\u003e \u003cp\u003eClinical Behaviour Change\u003c\/p\u003e \u003cp\u003eDisease Mapping\u003c\/p\u003e \u003cp\u003eDisease Surveillance\u003c\/p\u003e \u003cp\u003eDisease and Clinical Trial Modelling\u003c\/p\u003e \u003cp\u003eEarly Detection Programs in Medical Care\u003c\/p\u003e \u003cp\u003eFisheries Stock Assessment\u003c\/p\u003e \u003cp\u003eHealth Care Policy and Management of Stroke, Breast Cancer, and Mental Health\u003c\/p\u003e \u003cp\u003eHealthcare Performance Reports\u003c\/p\u003e \u003cp\u003eIntercalibration Studies\u003c\/p\u003e \u003cp\u003eMonitoring of Safety in EU Railways\u003c\/p\u003e \u003cp\u003eMultiple Modes in Proficiency Test Data\u003c\/p\u003e \u003cp\u003ePatient Opinion Measures\u003c\/p\u003e \u003cp\u003ePopulation Characteristics of Proficiency Test Data\u003c\/p\u003e \u003cp\u003eQuality in Critical Care Medicine\u003c\/p\u003e \u003cp\u003eSampling sediments in the Marine Environment\u003c\/p\u003e \u003cp\u003eStatistical Issues in Vaccine Safety Evaluation\u003c\/p\u003e \u003cp\u003eStatistical Process Control in Clinical Medicine\u003c\/p\u003e \u003cp\u003e\u003cb\u003eManagement of Quality \u0026amp; Business Statistics\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAttractive Quality\u003c\/p\u003e \u003cp\u003eBenchmarking in Project Definition\u003c\/p\u003e \u003cp\u003eBrainstorming\u003c\/p\u003e \u003cp\u003eCause and Effect Diagrams \u003c\/p\u003e \u003cp\u003eChange Management\u003c\/p\u003e \u003cp\u003eConcept Selection Matrices\u003c\/p\u003e \u003cp\u003eContingency Table\u003c\/p\u003e \u003cp\u003eContingency Table,Square\u003c\/p\u003e \u003cp\u003eCost of Quality\u003c\/p\u003e \u003cp\u003eCreativity tools \u003c\/p\u003e \u003cp\u003eCritical-To-Quality matrices\u003c\/p\u003e \u003cp\u003eData and Information Quality\u003c\/p\u003e \u003cp\u003eDirected Evolution +B35\u003c\/p\u003e \u003cp\u003eError proofing Healthcare\u003c\/p\u003e \u003cp\u003eFactor Relationship Diagrams \u003c\/p\u003e \u003cp\u003eFailure Modes and Effects Analysis\u003c\/p\u003e \u003cp\u003eKaizen\u003c\/p\u003e \u003cp\u003eLean Accounting\u003c\/p\u003e \u003cp\u003eLean Methods, Creating Flow with\u003c\/p\u003e \u003cp\u003eMulti-vari Charts\u003c\/p\u003e \u003cp\u003eOrganizational Assessment Models\u003c\/p\u003e \u003cp\u003ePolicy Deployment Drives Performance Improvement\u003c\/p\u003e \u003cp\u003eProcess Maps and Statistics\u003c\/p\u003e \u003cp\u003eProcess Maps: Construction of\u003c\/p\u003e \u003cp\u003eProcess Reengineering\u003c\/p\u003e \u003cp\u003eProject management : Stage Gate Approach to\u003c\/p\u003e \u003cp\u003eQuality Function Deployment \u003c\/p\u003e \u003cp\u003eQuality Management, Overview\u003c\/p\u003e \u003cp\u003eScorecards\u003c\/p\u003e \u003cp\u003eSix Sigma\u003c\/p\u003e \u003cp\u003eStatistical Efficiency\u003c\/p\u003e \u003cp\u003eStatistical quality control \u003c\/p\u003e \u003cp\u003eTarget costing\u003c\/p\u003e \u003cp\u003eTeam building\u003c\/p\u003e \u003cp\u003eTheory of constraints \u003c\/p\u003e \u003cp\u003eTotal Productive maintenance\u003c\/p\u003e \u003cp\u003eTotal Quality Management (TQM)\u003c\/p\u003e \u003cp\u003eValue-stream analysis  in Quality Management\u003c\/p\u003e \u003cp\u003eWork out\u003c\/p\u003e \u003cp\u003e\u003cb\u003eProcess Capability \u0026amp; Measurement Systems Analysis\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCalibration\u003c\/p\u003e \u003cp\u003eCapability Indices for Multiple Stream Processes\u003c\/p\u003e \u003cp\u003eCapability Measures for Measurement Systems Analysis \u003c\/p\u003e \u003cp\u003eComparison of Multivariate Process Capability Indices\u003c\/p\u003e \u003cp\u003eControl Charts and Process Capability\u003c\/p\u003e \u003cp\u003eCp, Cpk\u003c\/p\u003e \u003cp\u003eDefects per Million Opportunities\u003c\/p\u003e \u003cp\u003eDefects per Unit\u003c\/p\u003e \u003cp\u003eGauge Repeatability and Reproducibility (R\u0026amp;R) Studies, Confidence Intervals for\u003c\/p\u003e \u003cp\u003eGauge Repeatability and Reproducibility (R\u0026amp;R) Studies, Destructive Testing\u003c\/p\u003e \u003cp\u003eGauge Repeatability and Reproducibility (R\u0026amp;R) Studies, Misclassification Rates\u003c\/p\u003e \u003cp\u003eGauge Repeatability and Reproducibility (R\u0026amp;R), Variance Components in\u003c\/p\u003e \u003cp\u003eInterlaboratory Comparisons\u003c\/p\u003e \u003cp\u003eMeasurement Error and Uncertainty\u003c\/p\u003e \u003cp\u003eMeasurement Systems Analysis, Attribute\u003c\/p\u003e \u003cp\u003eMeasurement Systems Analysis, Overview\u003c\/p\u003e \u003cp\u003ePp, Ppk\u003c\/p\u003e \u003cp\u003eProcess Capability Indices, Alternative to\u003c\/p\u003e \u003cp\u003eProcess Capability Indices, Bayesian Estimation of\u003c\/p\u003e \u003cp\u003eProcess Capability Indices, Multivariate\u003c\/p\u003e \u003cp\u003eProcess Capability Indices, Non-normal\u003c\/p\u003e \u003cp\u003eProcess Capability Indices, Nonparametric\u003c\/p\u003e \u003cp\u003eProcess Capability Plots\u003c\/p\u003e \u003cp\u003eProcess Capability, Error in Estimating of\u003c\/p\u003e \u003cp\u003eProcess Yield\u003c\/p\u003e \u003cp\u003eSigma Level of a Process\u003c\/p\u003e \u003cp\u003eSkewed Process Capability Indices\u003c\/p\u003e \u003cp\u003eStatistical Process Control, Multivariate\u003c\/p\u003e \u003cp\u003eThe Comparison of Process Capability Indices\u003c\/p\u003e \u003cp\u003eYield Surface Modeling\u003c\/p\u003e \u003cp\u003e\u003cb\u003eProcess Control\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eARIMA Modeling\u003c\/p\u003e \u003cp\u003eAutocorrelated Data\u003c\/p\u003e \u003cp\u003eAverage Run Lengths and Operating Characteristic Curves\u003c\/p\u003e \u003cp\u003eChange Point Methods\u003c\/p\u003e \u003cp\u003eControl Charts for Attributes\u003c\/p\u003e \u003cp\u003eControl Charts for Batch Processes\u003c\/p\u003e \u003cp\u003eControl Charts for Short Production Runs\u003c\/p\u003e \u003cp\u003eControl Charts for the Mean\u003c\/p\u003e \u003cp\u003eControl Charts for the Standard Deviation\u003c\/p\u003e \u003cp\u003eControl Charts, Nonparametric\u003c\/p\u003e \u003cp\u003eControl Charts, Overview\u003c\/p\u003e \u003cp\u003eControl Charts, Selection of\u003c\/p\u003e \u003cp\u003eCumulative Sum (CUSUM) Chart\u003c\/p\u003e \u003cp\u003eEconomic Design of Control Charts\u003c\/p\u003e \u003cp\u003eEngineering Process Control \u003c\/p\u003e \u003cp\u003eExponentially Weighted Moving Average Control Chart\u003c\/p\u003e \u003cp\u003eFeed-Back Control\u003c\/p\u003e \u003cp\u003eHotelling’s T2 Chart\u003c\/p\u003e \u003cp\u003eInterpretation of Multivariate Control Charts\u003c\/p\u003e \u003cp\u003eMoving Range and R Charts\u003c\/p\u003e \u003cp\u003eMultivariate Charts for Variability\u003c\/p\u003e \u003cp\u003eMultivariate Control Charts Overview\u003c\/p\u003e \u003cp\u003eMultivariate Cumulative Sum (CUSUM) Chart \u003c\/p\u003e \u003cp\u003eMultivariate EWMA Control Chart\u003c\/p\u003e \u003cp\u003eNeural Networks: Construction and Evaluation\u003c\/p\u003e \u003cp\u003ePrecontrol\u003c\/p\u003e \u003cp\u003eProfile Monitoring\u003c\/p\u003e \u003cp\u003eRegression Control Charts\u003c\/p\u003e \u003cp\u003eVariable Sampling Rate Control Charts\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReliability: Life Cycle \u0026amp; Warranty Cost Prediction\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAge Dependent Minimal Repair and Maintenance\u003c\/p\u003e \u003cp\u003eAnalysis of Recurrent Events from Repairable Systems\u003c\/p\u003e \u003cp\u003eBurn-In and Maintenance Policies\u003c\/p\u003e \u003cp\u003eCumulative Damage Models Based on Gamma Processes\u003c\/p\u003e \u003cp\u003eDegradation Models\u003c\/p\u003e \u003cp\u003eExpert Opinion in Reliability\u003c\/p\u003e \u003cp\u003eGeneral Minimum Repair Models\u003c\/p\u003e \u003cp\u003eGlobal and Dynamic Information Measures for Reliability\u003c\/p\u003e \u003cp\u003eGroup Maintenance Policies\u003c\/p\u003e \u003cp\u003eImperfect Repair\u003c\/p\u003e \u003cp\u003eInspection Policies for Reliability\u003c\/p\u003e \u003cp\u003eLife Cycle Costs and Reliability Engineering\u003c\/p\u003e \u003cp\u003eLoad Sharing Models\u003c\/p\u003e \u003cp\u003eMaintenance Optimization\u003c\/p\u003e \u003cp\u003eMaintenance Optimization in Random Environments.\u003c\/p\u003e \u003cp\u003eMarkov Renewal Processes in Reliability Modeling\u003c\/p\u003e \u003cp\u003eMasked Failure Data: Competing Risks\u003c\/p\u003e \u003cp\u003eMultiattribute Warranty Policies\u003c\/p\u003e \u003cp\u003eMulticomponent Maintenance\u003c\/p\u003e \u003cp\u003eMulti-State Reliability Theory\u003c\/p\u003e \u003cp\u003eMultivariate Age and Multivariate Renewal Replacement\u003c\/p\u003e \u003cp\u003eMultivariate Imperfect Repair Models\u003c\/p\u003e \u003cp\u003eNonparametric and Semiparametric Bayesian Reliability Analysis\u003c\/p\u003e \u003cp\u003eNonparametric Methods for Analysis of Repair Data\u003c\/p\u003e \u003cp\u003eReliability Growth Modeling\u003c\/p\u003e \u003cp\u003eRepair Data, sets of: how to Graph, Analyse, and Compare\u003c\/p\u003e \u003cp\u003eReplacement Strategies\u003c\/p\u003e \u003cp\u003eStationary Replacement Strategies\u003c\/p\u003e \u003cp\u003eSystem Availability\u003c\/p\u003e \u003cp\u003eTotal Time on Tests Plots\u003c\/p\u003e \u003cp\u003eWarranty Claims and Costs: Statistical Analysis of\u003c\/p\u003e \u003cp\u003eWarranty Cost Analysis\u003c\/p\u003e \u003cp\u003eWarranty Cost Prediction Based on Warranty Data\u003c\/p\u003e \u003cp\u003eWarranty Modeling\u003c\/p\u003e \u003cp\u003eWarranty Servicing\u003c\/p\u003e \u003cp\u003eWarranty: Usage and Wear Process for\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReliability: Life Distribution Modeling \u0026amp; Accelerated Testing\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests, Bayesian Models\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests: Analysis with Competing Failure Modes\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests: Nonparametric Approach\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests:Bayesian Design\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests:Classical Methods for Design and Analysis\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests:Designs Comparison with a Bayesian Framework\u003c\/p\u003e \u003cp\u003eAccelerated Life Tests:Step Stress (Classical Methods)\u003c\/p\u003e \u003cp\u003eCumulative hazard function\u003c\/p\u003e \u003cp\u003eDesign for Reliability\u003c\/p\u003e \u003cp\u003eHazard function\u003c\/p\u003e \u003cp\u003eIntensity function\u003c\/p\u003e \u003cp\u003eLife Testing from a Bayesian Perspective\u003c\/p\u003e \u003cp\u003eMasked Failure Data\u003c\/p\u003e \u003cp\u003eMean residual life\u003c\/p\u003e \u003cp\u003eMean time between failures\u003c\/p\u003e \u003cp\u003eMean time to failure\u003c\/p\u003e \u003cp\u003eMean time to repair\u003c\/p\u003e \u003cp\u003ePrediction of Expected Fatigue Lives of Fiber Reinforced Plastic Joints\u003c\/p\u003e \u003cp\u003eProportional hazard model\u003c\/p\u003e \u003cp\u003eRate of occurrence of failures\u003c\/p\u003e \u003cp\u003eReliability function\u003c\/p\u003e \u003cp\u003eSoftware Failure Data Analysis\u003c\/p\u003e \u003cp\u003eThe Cox Proportional Hazard Model\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSampling\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAcceptance Sampling in Modern Industrial Environments\u003c\/p\u003e \u003cp\u003eAdaptive and Spatial Sampling Designs.\u003c\/p\u003e \u003cp\u003eAttribute Sampling Schemes in International Standards\u003c\/p\u003e \u003cp\u003eAttributes Sampling Under Classification Error\u003c\/p\u003e \u003cp\u003eContinuous Sampling\u003c\/p\u003e \u003cp\u003eData Management in Survey Sampling\u003c\/p\u003e \u003cp\u003eDatabase Systems for Acceptance Sampling\u003c\/p\u003e \u003cp\u003eDesign and Testing of Questionnaires\u003c\/p\u003e \u003cp\u003eEconomic Sampling Schemes\u003c\/p\u003e \u003cp\u003eInternal and External Quality Measures\u003c\/p\u003e \u003cp\u003eMultiple Sampling Plans\u003c\/p\u003e \u003cp\u003ePrior Information in Sampling Schemes.\u003c\/p\u003e \u003cp\u003eProcessing of Survey Data\u003c\/p\u003e \u003cp\u003eRectification Sampling Schemes\u003c\/p\u003e \u003cp\u003eReliability Sampling\u003c\/p\u003e \u003cp\u003eSampling Designs in Surveys\u003c\/p\u003e \u003cp\u003eSampling from Virtual Populations\u003c\/p\u003e \u003cp\u003eSampling in Data Mining (subsampling)\u003c\/p\u003e \u003cp\u003eSampling in Implementation of Statistical Process Control\u003c\/p\u003e \u003cp\u003eSampling in Industrial Standards\u003c\/p\u003e \u003cp\u003eSampling in Pharmaceutical and Chemical Industries\u003c\/p\u003e \u003cp\u003eSampling in Semiconductor Manufacturing.\u003c\/p\u003e \u003cp\u003eSampling in Software Development\u003c\/p\u003e \u003cp\u003eSampling Inspection of Products\u003c\/p\u003e \u003cp\u003eSampling Inspection of Products and Statistical Process Control\u003c\/p\u003e \u003cp\u003eSelection and Validation of Response Scales\u003c\/p\u003e \u003cp\u003eSERVQUAL Surveys\u003c\/p\u003e \u003cp\u003eSingle Sampling by Attributes and by Variables.\u003c\/p\u003e \u003cp\u003eSkip-lot Sampling and Chain Sampling\u003c\/p\u003e \u003cp\u003eStatistical Analysis of Survey Data\u003c\/p\u003e \u003cp\u003eSurvey Error\u003c\/p\u003e \u003cp\u003eSurvey Quality and Survey Ethics\u003c\/p\u003e \u003cp\u003eVariables Sampling Schemes in International Standards\u003c\/p\u003e \u003cp\u003eVariables Sampling Under Measurement Error.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eStatistical and Stochastic Modeling\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAccelerated Life Models\u003c\/p\u003e \u003cp\u003eAging and Positive Dependance\u003c\/p\u003e \u003cp\u003eApplications of Extreme Statistics in Science and Engineering\u003c\/p\u003e \u003cp\u003eAvailability Models\u003c\/p\u003e \u003cp\u003eBayesian Control Charts\u003c\/p\u003e \u003cp\u003eBayesian Networks\u003c\/p\u003e \u003cp\u003eBayesian Reliability Analysis\u003c\/p\u003e \u003cp\u003eBayesian Reliability Demonstration\u003c\/p\u003e \u003cp\u003eBrownian Motion\u003c\/p\u003e \u003cp\u003eCausality\u003c\/p\u003e \u003cp\u003eChange-Point Models\u003c\/p\u003e \u003cp\u003eCharacterization in Reliability\u003c\/p\u003e \u003cp\u003eCompeting Risks\u003c\/p\u003e \u003cp\u003eDamage Processes\u003c\/p\u003e \u003cp\u003eDegradation and Failure\u003c\/p\u003e \u003cp\u003eDegradation Processes\u003c\/p\u003e \u003cp\u003eDesign of Bayesian Reliability Experiments\u003c\/p\u003e \u003cp\u003eEmpirical Bayes Estimation of Reliability\u003c\/p\u003e \u003cp\u003eHierarchical Markov Chain Monte Carlo (MCMC) for Bayesian System Reliability\u003c\/p\u003e \u003cp\u003eLevy Processes\u003c\/p\u003e \u003cp\u003eMaintenance and Markov Decision Models\u003c\/p\u003e \u003cp\u003eMarkov Processes\u003c\/p\u003e \u003cp\u003eMasked Failure Data: Bayesian Modeling\u003c\/p\u003e \u003cp\u003eMultivariate Mixtures Models- Related Aging and Dependance Properties\u003c\/p\u003e \u003cp\u003eMultivariate Stochastic Orders and Aging\u003c\/p\u003e \u003cp\u003ePhysical Degradation Models\u003c\/p\u003e \u003cp\u003ePoisson Processes\u003c\/p\u003e \u003cp\u003ePrecedence Tests\u003c\/p\u003e \u003cp\u003ePrior Distribution Elicitation\u003c\/p\u003e \u003cp\u003eRandom Evolutions toward Applications\u003c\/p\u003e \u003cp\u003eRenewal Theory\u003c\/p\u003e \u003cp\u003eRisk Analysis,Extremes in\u003c\/p\u003e \u003cp\u003eRisk Processes\u003c\/p\u003e \u003cp\u003eScan Statistics\u003c\/p\u003e \u003cp\u003eSoftware Reliability Modeling and Analysis\u003c\/p\u003e \u003cp\u003eSoftware Reliability: Bayesian Analysis\u003c\/p\u003e \u003cp\u003eStatistical Process Control, Bayesian\u003c\/p\u003e \u003cp\u003eStochastic Deterioration\u003c\/p\u003e \u003cp\u003eStochastic Orders and Aging Notions\u003c\/p\u003e \u003cp\u003eSubjective Life Models\u003c\/p\u003e \u003cp\u003eSystem Signatures\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSystem Reliability\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBlock Replacement\u003c\/p\u003e \u003cp\u003eCoherent Systems\u003c\/p\u003e \u003cp\u003eComponent Reliability Importance\u003c\/p\u003e \u003cp\u003eFault Trees\u003c\/p\u003e \u003cp\u003eFlowgraph models\u003c\/p\u003e \u003cp\u003eGenetic Algorithms in Reliability\u003c\/p\u003e \u003cp\u003eImperfect Repair, Counting Processes\u003c\/p\u003e \u003cp\u003eIntensity Functions for Nonhomogeneous Poisson Processes\u003c\/p\u003e \u003cp\u003ek-out-of-n Systems\u003c\/p\u003e \u003cp\u003eModules and Modular Decomposition\u003c\/p\u003e \u003cp\u003eParallel, Series, and SeriesParallel Systems\u003c\/p\u003e \u003cp\u003ePath Sets and Cut Sets  in System Reliability Modeling\u003c\/p\u003e \u003cp\u003eQueues in Reliability\u003c\/p\u003e \u003cp\u003eReliability Allocation\u003c\/p\u003e \u003cp\u003eReliability Databases\u003c\/p\u003e \u003cp\u003eReliability of Redundant Systems\u003c\/p\u003e \u003cp\u003eReliability Optimization\u003c\/p\u003e \u003cp\u003eReliability, Safety, and Risk Management\u003c\/p\u003e \u003cp\u003eRepairable Systems Reliability\u003c\/p\u003e \u003cp\u003eRepairable systems, statistical inference\u003c\/p\u003e \u003cp\u003eRepairable Systems: Bayesian analysis\u003c\/p\u003e \u003cp\u003eStress-Strength Model\u003c\/p\u003e \u003cp\u003eSystem Downtime Distributions\u003c\/p\u003e \u003cp\u003eSystem Reliability: Computational Algebra Methods\u003c\/p\u003e \u003cp\u003eSystem Reliability:Monte-Carlo Estimation.\u003c\/p\u003e  \"I must say that this encyclopedia is a must-have for everyone working on quality and reliability. It is an excellent source of information.\" (\u003ci\u003eTechnometrics,\u003c\/i\u003e May 2010)\u003cbr\u003e \u003cbr\u003e  \"[The text] could provide the initial go-to text for any person researching or working within the field of quality. The production is good, with a nice layout and well bound pages … .The journey through the pages is often interrupted by an unlikely article that catches the attention which is the delight of paper texts.\" (\u003ci\u003eAccreditation and Quality Assurance\u003c\/i\u003e, February 2009)  \u003cb\u003eEditors-in-Chief\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eFabrizio Ruggeri,\u003c\/b\u003e 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRon S. Kenett,\u003c\/b\u003e 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\u0026amp;T, hp, EDS, SanDisk, IBM and Amdocs. His career has combined academic positions with activity in the industrial and business sector.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eFrederick W. Faltin\u003c\/b\u003e, The Faltin Group, Cody, WY, USAMr. Faltin’s interests include Managing Six Sigma, Design for Six Sigma, Business Process Simulation \u0026amp; 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 \u0026amp; Productivity Research Conference and the Fall Technical Conference. Mr. Faltin has published dozens of papers on applications of mathematics \u0026amp; 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eEditors\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBasics Statistics\u003c\/p\u003e \u003cp\u003e\u003cb\u003eJeroen de Mast\u003c\/b\u003e, \u003ci\u003eUniversity of Amsterdam,\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThe Netherlands\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eComputationally Intensive Methods \u0026amp; Simulation\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSimon Wilson\u003c\/b\u003e, \u003ci\u003eTrinity College Dublin, Ireland\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eDesign of Experiments \u0026amp; Robust Design\u003c\/p\u003e \u003cp\u003e\u003cb\u003eDavid Steinberg\u003c\/b\u003e, \u003ci\u003eTel Aviv University, Israel\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eHealth, Safety \u0026amp; Environmental Applications\u003c\/p\u003e \u003cp\u003e\u003cb\u003eTony Greenfield\u003c\/b\u003e, \u003ci\u003eGreenfield Research, UK\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eManagement of Quality \u0026amp; Business Statistics\u003c\/p\u003e \u003cp\u003e\u003cb\u003eBlanton Godfrey\u003c\/b\u003e, \u003ci\u003eCollege of Textiles, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRamon Leon\u003c\/b\u003e, \u003ci\u003eUniversity of Tennessee, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eProcess Capability \u0026amp; Measurement Systems Analysis\u003c\/p\u003e \u003cp\u003e\u003cb\u003eConnie Borror\u003c\/b\u003e, \u003ci\u003eUniversity of Illinois, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eProcess Control\u003c\/p\u003e \u003cp\u003e\u003cb\u003eMike Adams\u003c\/b\u003e, \u003ci\u003eUniversity of Alabama, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eReliability: Life Cycle \u0026amp; Warranty Cost Prediction\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRefik Soyer\u003c\/b\u003e, \u003ci\u003eGeorge Washington University, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eReliability: Life Distribution Modeling \u0026amp; Accelerated Testing\u003c\/p\u003e \u003cp\u003e\u003cb\u003eTom Mazzuchi\u003c\/b\u003e, \u003ci\u003eGeorge Washington University, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSampling\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRainer Göb\u003c\/b\u003e, \u003ci\u003eUniversity of Wuerzberg, Germany\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eStatistical and Stochastic Modelling\u003c\/p\u003e \u003cp\u003e\u003cb\u003eShelley Zacks\u003c\/b\u003e, \u003ci\u003eBinghamton University, USA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSystem Reliability\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSteven Rigdon\u003c\/b\u003e, \u003ci\u003eSouthern Illinois University, USA\u003c\/i\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989131018469,"sku":"NP9780470018613","price":1734.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470018613.jpg?v=1761782920","url":"https:\/\/k12savings.com\/products\/encyclopedia-of-statistics-in-quality-and-reliability-isbn-9780470018613","provider":"K12savings","version":"1.0","type":"link"}