Encyclopedia of Statistics in Quality and Reliability

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.
<p>Basic Statistics</p>
<p>Assignable cause</p>
<p>Autocorrelation function</p>
<p>Bias of an estimator</p>
<p>Box and Cox transformation</p>
<p>Coefficient of determination (R2)</p>
<p>Collinearity</p>
<p>Confidence intervals</p>
<p>Correlation</p>
<p>Covariance</p>
<p>Covariate</p>
<p>Cumulative distribution function (CDF)</p>
<p>Data collection</p>
<p>Degrees of freedom</p>
<p>Dependence</p>
<p>Descriptive Statistics</p>
<p>Estimation</p>
<p>Expectation</p>
<p>Exploratory data analysis</p>
<p>Exponentially weighted moving average (EWMA)</p>
<p>Graphical representation of data</p>
<p>Heteroscedasticity</p>
<p>Homogeneity of Variances; Homoscedasticity</p>
<p>Hotelling s T2</p>
<p>Hypothesis testing</p>
<p>Kurtosis</p>
<p>Lack of fit</p>
<p>Laws of large numbers</p>
<p>Least squares estimation</p>
<p>Leverage</p>
<p>Maximum likelihood</p>
<p>Mean square error</p>
<p>Measures of Association</p>
<p>Measures of Location</p>
<p>Measures of Scale</p>
<p>Missing data and imputation</p>
<p>Moments</p>
<p>Monte Carlo methods</p>
<p>Moving averages</p>
<p>Multi–vari chart</p>
<p>Multivariate analysis</p>
<p>Nonparametric Tests</p>
<p>Normal distribution</p>
<p>Normality Tests</p>
<p>Observational studies</p>
<p>Outliers</p>
<p>Overview of Statistics</p>
<p>Parametric tests</p>
<p>Pareto chart</p>
<p>Pooled variance, pooled estimate</p>
<p>Power</p>
<p>Probability density function (PDF)</p>
<p>Probability density functions</p>
<p>Probability plots</p>
<p>Probability theory</p>
<p>P–values</p>
<p>Quantiles</p>
<p>Quartiles</p>
<p>Residuals</p>
<p>Runs, runs tests</p>
<p>Sample Size Determination</p>
<p>Sigma Metric</p>
<p>Significance level</p>
<p>Six Sigma Method</p>
<p>Skewness</p>
<p>Standard error</p>
<p>Statistical Methods for Counts, Rates and Proportions</p>
<p>Sum of squares</p>
<p>Time series analysis</p>
<p>Transfer function</p>
<p>Trimmed mean</p>
<p>Variables</p>
<p>Variance</p>
<p>Variance components</p>
<p>Computationally Intensive Methods &amp; Simulation</p>
<p>Asymptotic&nbsp; Reliability Analysis of Very Large Systems</p>
<p>Bayesian networks in reliability</p>
<p>Bayesian robustness: theory and computation</p>
<p>Bootstrap And Jacknife: Overview</p>
<p>Classification and Regression Tree Methods</p>
<p>Computational Issues in Network Reliability</p>
<p>Convergence and Mixing in Markov Chain Monte Carlo</p>
<p>Data Mining in Quality and Reliability</p>
<p>decision search via simulation</p>
<p>Density and failure rate estimation</p>
<p>Dirichlet process, Simulation of</p>
<p>Discrete event simulation for reliability prediction</p>
<p>Dynamic ProgrammingMethods in Repair and Replacement</p>
<p>Evaluation techniques in data mining</p>
<p>Expectation Maximisation Algorithm</p>
<p>Failure Modes and Effects Analysis, Implementation of</p>
<p>Fault tree analysis for large systems</p>
<p>Integrating computer and physical experiment data</p>
<p>Laplace approximations in Bayesian lifetime analysis</p>
<p>Levy Processes, Simulation of</p>
<p>Life Distributions, Simulation of</p>
<p>Lifetime Distributions, Optimization Methods for</p>
<p>Markov chain Monte Carlo, Introduction</p>
<p>Monte Carlo Methods: Univariate and Multivariate</p>
<p>Neural networks in Statistical Process Control</p>
<p>Optimal Reliability Design– Algorithms and Comparisons</p>
<p>Optimal Reliability Design– Modelling</p>
<p>Perfect Sampling</p>
<p>Polya Trees and Their Use in Reliability and Survival Analysis</p>
<p>quality control, Computing in</p>
<p>quandrature and numerical integration</p>
<p>Resampling for lifetime distributions</p>
<p>Simulation of the beta–Stacy process</p>
<p>Smoothed Function Estimation for Censored Data</p>
<p>Splines and other meta–models in reliability analysis</p>
<p>Survival Analysis , Nonparametric</p>
<p>Design of Experiments &amp; Robust Design</p>
<p>Aliasing in Fractional Designs</p>
<p>Analysis of Variance</p>
<p>Assessment of Experimental Designs</p>
<p>Bergman–Hynen Method for Dispersion Effects</p>
<p>Blocking</p>
<p>Box–Behnken Designs</p>
<p>Box–Meyer Method for Dispersion Effects</p>
<p>Center Points</p>
<p>Central Composite Designs</p>
<p>Computer Experiments</p>
<p>Dispersion Effects</p>
<p>Factorial Designs, Resolution of</p>
<p>Factorial Experiments</p>
<p>Foldover Designs</p>
<p>Fractional Factorial Designs</p>
<p>Gauge Repeatability and Reproducibility (R&amp;R) Studies</p>
<p>Generalized Linear Models</p>
<p>Half–normal Plot</p>
<p>Harvey′s Method for Dispersion Effects</p>
<p>Incomplete Block Designs</p>
<p>Interactions</p>
<p>Latin Hypercube Designs</p>
<p>Latin Squares and Related Experimental Designs</p>
<p>Lenth′s Method for the Analysis of Unreplicated Experiments</p>
<p>Main Effect Designs</p>
<p>Main Effects</p>
<p>Minimum Aberration</p>
<p>Mixture Experiments</p>
<p>Optimal Design</p>
<p>Orthogonal Arrays</p>
<p>Performance Measures for Robust Design</p>
<p>Plackett– Burman Designs</p>
<p>Product Array Designs</p>
<p>Projectivity in Experimental Designs</p>
<p>Randomization in Experimental Designs</p>
<p>Response Surface Methodology</p>
<p>Ridge Analysis in Experimental Design</p>
<p>Robust Design</p>
<p>Rotatable Designs and Rotatability</p>
<p>Sample–Size Determination in Experimental Designs</p>
<p>Screening Designs</p>
<p>Sequential Experimentation</p>
<p>Signal Response Systems</p>
<p>Signal–to–Noise Ratios for Robust Design</p>
<p>Split–Plot Designs</p>
<p>Supersaturated Designs</p>
<p>Tolerance Design</p>
<p>Uniform Experimental Designs</p>
<p>Health, Safety &amp; Environmental Applications</p>
<p>Bias in Modeling and Monitoring Health Outcomes</p>
<p>Case Series Analysis, Vaccine Safety Evaluation Using a Suitable Motivating Example.</p>
<p>Case–control Studies</p>
<p>Clinical Behaviour Change</p>
<p>Disease Mapping</p>
<p>Disease Surveillance</p>
<p>Disease and Clinical Trial Modelling</p>
<p>Early Detection Programs in Medical Care</p>
<p>Fisheries Stock Assessment</p>
<p>Health Care Policy and Management of Stroke, Breast Cancer, and Mental Health</p>
<p>Healthcare Performance Reports</p>
<p>Intercalibration Studies</p>
<p>Monitoring of Safety in EU Railways</p>
<p>Multiple Modes in Proficiency Test Data</p>
<p>Patient Opinion Measures</p>
<p>Population Characteristics of Proficiency Test Data</p>
<p>Quality in Critical Care Medicine</p>
<p>Sampling sediments in the Marine Environment</p>
<p>Statistical Issues in Vaccine Safety Evaluation</p>
<p>Statistical Process Control in Clinical Medicine</p>
<p>Management of Quality &amp; Business Statistics</p>
<p>Attractive Quality</p>
<p>Benchmarking in Project Definition</p>
<p>Brainstorming</p>
<p>Cause and Effect Diagrams&nbsp;</p>
<p>Change Management</p>
<p>Concept Selection Matrices</p>
<p>Contingency Table</p>
<p>Contingency Table,Square</p>
<p>Cost of Quality</p>
<p>Creativity tools&nbsp;</p>
<p>Critical–To–Quality matrices</p>
<p>Data and Information Quality</p>
<p>Directed Evolution +B35</p>
<p>Error proofing Healthcare</p>
<p>Factor Relationship Diagrams&nbsp;</p>
<p>Failure Modes and Effects Analysis</p>
<p>Kaizen</p>
<p>Lean Accounting</p>
<p>Lean Methods, Creating Flow with</p>
<p>Multi–vari Charts</p>
<p>Organizational Assessment Models</p>
<p>Policy Deployment Drives Performance Improvement</p>
<p>Process Maps and Statistics</p>
<p>Process Maps: Construction of</p>
<p>Process Reengineering</p>
<p>Project management : Stage Gate Approach to</p>
<p>Quality Function Deployment&nbsp;</p>
<p>Quality Management, Overview</p>
<p>Scorecards</p>
<p>Six Sigma</p>
<p>Statistical Efficiency</p>
<p>Statistical quality control&nbsp;</p>
<p>Target costing</p>
<p>Team building</p>
<p>Theory of constraints&nbsp;</p>
<p>Total Productive maintenance</p>
<p>Total Quality Management (TQM)</p>
<p>Value–stream analysis&nbsp; in Quality Management</p>
<p>Work out</p>
<p>Process Capability &amp; Measurement Systems Analysis</p>
<p>Calibration</p>
<p>Capability Indices for Multiple Stream Processes</p>
<p>Capability Measures for Measurement Systems Analysis&nbsp;</p>
<p>Comparison of Multivariate Process Capability Indices</p>
<p>Control Charts and Process Capability</p>
<p>Cp, Cpk</p>
<p>Defects per Million Opportunities</p>
<p>Defects per Unit</p>
<p>Gauge Repeatability and Reproducibility (R&amp;R) Studies, Confidence Intervals for</p>
<p>Gauge Repeatability and Reproducibility (R&amp;R) Studies, Destructive Testing</p>
<p>Gauge Repeatability and Reproducibility (R&amp;R) Studies, Misclassification Rates</p>
<p>Gauge Repeatability and Reproducibility (R&amp;R), Variance Components in</p>
<p>Interlaboratory Comparisons</p>
<p>Measurement Error and Uncertainty</p>
<p>Measurement Systems Analysis, Attribute</p>
<p>Measurement Systems Analysis, Overview</p>
<p>Pp, Ppk</p>
<p>Process Capability Indices, Alternative to</p>
<p>Process Capability Indices, Bayesian Estimation of</p>
<p>Process Capability Indices, Multivariate</p>
<p>Process Capability Indices, Non–normal</p>
<p>Process Capability Indices, Nonparametric</p>
<p>Process Capability Plots</p>
<p>Process Capability, Error in Estimating of</p>
<p>Process Yield</p>
<p>Sigma Level of a Process</p>
<p>Skewed Process Capability Indices</p>
<p>Statistical Process Control, Multivariate</p>
<p>The Comparison of Process Capability Indices</p>
<p>Yield Surface Modeling</p>
<p>Process Control</p>
<p>ARIMA Modeling</p>
<p>Autocorrelated Data</p>
<p>Average Run Lengths and Operating Characteristic Curves</p>
<p>Change Point Methods</p>
<p>Control Charts for Attributes</p>
<p>Control Charts for Batch Processes</p>
<p>Control Charts for Short Production Runs</p>
<p>Control Charts for the Mean</p>
<p>Control Charts for the Standard Deviation</p>
<p>Control Charts, Nonparametric</p>
<p>Control Charts, Overview</p>
<p>Control Charts, Selection of</p>
<p>Cumulative Sum (CUSUM) Chart</p>
<p>Economic Design of Control Charts</p>
<p>Engineering Process Control&nbsp;</p>
<p>Exponentially Weighted Moving Average Control Chart</p>
<p>Feed–Back Control</p>
<p>Hotelling s T2 Chart</p>
<p>Interpretation of Multivariate Control Charts</p>
<p>Moving Range and R Charts</p>
<p>Multivariate Charts for Variability</p>
<p>Multivariate Control Charts Overview</p>
<p>Multivariate Cumulative Sum (CUSUM) Chart&nbsp;</p>
<p>Multivariate EWMA Control Chart</p>
<p>Neural Networks: Construction and Evaluation</p>
<p>Precontrol</p>
<p>Profile Monitoring</p>
<p>Regression Control Charts</p>
<p>Variable Sampling Rate Control Charts</p>
<p>Reliability: Life Cycle &amp; Warranty Cost Prediction</p>
<p>Age Dependent Minimal Repair and Maintenance</p>
<p>Analysis of Recurrent Events from Repairable Systems</p>
<p>Burn–In and Maintenance Policies</p>
<p>Cumulative Damage Models Based on Gamma Processes</p>
<p>Degradation Models</p>
<p>Expert Opinion in Reliability</p>
<p>General Minimum Repair Models</p>
<p>Global and Dynamic Information Measures for Reliability</p>
<p>Group Maintenance Policies</p>
<p>Imperfect Repair</p>
<p>Inspection Policies for Reliability</p>
<p>Life Cycle Costs and Reliability Engineering</p>
<p>Load Sharing Models</p>
<p>Maintenance Optimization</p>
<p>Maintenance Optimization in Random Environments.</p>
<p>Markov Renewal Processes in Reliability Modeling</p>
<p>Masked Failure Data: Competing Risks</p>
<p>Multiattribute Warranty Policies</p>
<p>Multicomponent Maintenance</p>
<p>Multi–State Reliability Theory</p>
<p>Multivariate Age and Multivariate Renewal Replacement</p>
<p>Multivariate Imperfect Repair Models</p>
<p>Nonparametric and Semiparametric Bayesian Reliability Analysis</p>
<p>Nonparametric Methods for Analysis of Repair Data</p>
<p>Reliability Growth Modeling</p>
<p>Repair Data, sets of: how to Graph, Analyse, and Compare</p>
<p>Replacement Strategies</p>
<p>Stationary Replacement Strategies</p>
<p>System Availability</p>
<p>Total Time on Tests Plots</p>
<p>Warranty Claims and Costs: Statistical Analysis of</p>
<p>Warranty Cost Analysis</p>
<p>Warranty Cost Prediction Based on Warranty Data</p>
<p>Warranty Modeling</p>
<p>Warranty Servicing</p>
<p>Warranty: Usage and Wear Process for</p>
<p>Reliability: Life Distribution Modeling &amp; Accelerated Testing</p>
<p>Accelerated Life Tests, Bayesian Models</p>
<p>Accelerated Life Tests: Analysis with Competing Failure Modes</p>
<p>Accelerated Life Tests: Nonparametric Approach</p>
<p>Accelerated Life Tests:Bayesian Design</p>
<p>Accelerated Life Tests:Classical Methods for Design and Analysis</p>
<p>Accelerated Life Tests:Designs Comparison with a Bayesian Framework</p>
<p>Accelerated Life Tests:Step Stress (Classical Methods)</p>
<p>Cumulative hazard function</p>
<p>Design for Reliability</p>
<p>Hazard function</p>
<p>Intensity function</p>
<p>Life Testing from a Bayesian Perspective</p>
<p>Masked Failure Data</p>
<p>Mean residual life</p>
<p>Mean time between failures</p>
<p>Mean time to failure</p>
<p>Mean time to repair</p>
<p>Prediction of Expected Fatigue Lives of Fiber Reinforced Plastic Joints</p>
<p>Proportional hazard model</p>
<p>Rate of occurrence of failures</p>
<p>Reliability function</p>
<p>Software Failure Data Analysis</p>
<p>The Cox Proportional Hazard Model</p>
<p>Sampling</p>
<p>Acceptance Sampling in Modern Industrial Environments</p>
<p>Adaptive and Spatial Sampling Designs.</p>
<p>Attribute Sampling Schemes in International Standards</p>
<p>Attributes Sampling Under Classification Error</p>
<p>Continuous Sampling</p>
<p>Data Management in Survey Sampling</p>
<p>Database Systems for Acceptance Sampling</p>
<p>Design and Testing of Questionnaires</p>
<p>Economic Sampling Schemes</p>
<p>Internal and External Quality Measures</p>
<p>Multiple Sampling Plans</p>
<p>Prior Information in Sampling Schemes.</p>
<p>Processing of Survey Data</p>
<p>Rectification Sampling Schemes</p>
<p>Reliability Sampling</p>
<p>Sampling Designs in Surveys</p>
<p>Sampling from Virtual Populations</p>
<p>Sampling in Data Mining (subsampling)</p>
<p>Sampling in Implementation of Statistical Process Control</p>
<p>Sampling in Industrial Standards</p>
<p>Sampling in Pharmaceutical and Chemical Industries</p>
<p>Sampling in Semiconductor Manufacturing.</p>
<p>Sampling in Software Development</p>
<p>Sampling Inspection of Products</p>
<p>Sampling Inspection of Products and Statistical Process Control</p>
<p>Selection and Validation of Response Scales</p>
<p>SERVQUAL Surveys</p>
<p>Single Sampling by Attributes and by Variables.</p>
<p>Skip–lot Sampling and Chain Sampling</p>
<p>Statistical Analysis of Survey Data</p>
<p>Survey Error</p>
<p>Survey Quality and Survey Ethics</p>
<p>Variables Sampling Schemes in International Standards</p>
<p>Variables Sampling Under Measurement Error.</p>
<p>Statistical and Stochastic Modeling</p>
<p>Accelerated Life Models</p>
<p>Aging and Positive Dependance</p>
<p>Applications of Extreme Statistics in Science and Engineering</p>
<p>Availability Models</p>
<p>Bayesian Control Charts</p>
<p>Bayesian Networks</p>
<p>Bayesian Reliability Analysis</p>
<p>Bayesian Reliability Demonstration</p>
<p>Brownian Motion</p>
<p>Causality</p>
<p>Change–Point Models</p>
<p>Characterization in Reliability</p>
<p>Competing Risks</p>
<p>Damage Processes</p>
<p>Degradation and Failure</p>
<p>Degradation Processes</p>
<p>Design of Bayesian Reliability Experiments</p>
<p>Empirical Bayes Estimation of Reliability</p>
<p>Hierarchical Markov Chain Monte Carlo (MCMC) for Bayesian System Reliability</p>
<p>Levy Processes</p>
<p>Maintenance and Markov Decision Models</p>
<p>Markov Processes</p>
<p>Masked Failure Data: Bayesian Modeling</p>
<p>Multivariate Mixtures Models– Related Aging and Dependance Properties</p>
<p>Multivariate Stochastic Orders and Aging</p>
<p>Physical Degradation Models</p>
<p>Poisson Processes</p>
<p>Precedence Tests</p>
<p>Prior Distribution Elicitation</p>
<p>Random Evolutions toward Applications</p>
<p>Renewal Theory</p>
<p>Risk Analysis,Extremes in</p>
<p>Risk Processes</p>
<p>Scan Statistics</p>
<p>Software Reliability Modeling and Analysis</p>
<p>Software Reliability: Bayesian Analysis</p>
<p>Statistical Process Control, Bayesian</p>
<p>Stochastic Deterioration</p>
<p>Stochastic Orders and Aging Notions</p>
<p>Subjective Life Models</p>
<p>System Signatures</p>
<p>System Reliability</p>
<p>Block Replacement</p>
<p>Coherent Systems</p>
<p>Component Reliability Importance</p>
<p>Fault Trees</p>
<p>Flowgraph models</p>
<p>Genetic Algorithms in Reliability</p>
<p>Imperfect Repair, Counting Processes</p>
<p>Intensity Functions for Nonhomogeneous Poisson Processes</p>
<p>k–out–of–n Systems</p>
<p>Modules and Modular Decomposition</p>
<p>Parallel, Series, and SeriesParallel Systems</p>
<p>Path Sets and Cut Sets&nbsp; in System Reliability Modeling</p>
<p>Queues in Reliability</p>
<p>Reliability Allocation</p>
<p>Reliability Databases</p>
<p>Reliability of Redundant Systems</p>
<p>Reliability Optimization</p>
<p>Reliability, Safety, and Risk Management</p>
<p>Repairable Systems Reliability</p>
<p>Repairable systems, statistical inference</p>
<p>Repairable Systems: Bayesian analysis</p>
<p>Stress–Strength Model</p>
<p>System Downtime Distributions</p>
<p>System Reliability: Computational Algebra Methods</p>
<p>System Reliability:Monte–Carlo Estimation.</p>