Industrial Statistics

Softcover Nachdruck of the original 1. Auflage 1997
ISBN: 978-3-7908-1042-4
Verlag: Physica Verlag

Buch, Englisch, 302 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 498 g

Reihe: Contributions to Statistics

Devoted to the growing impact of statistical methodology and statistical computing in industry the aim of this book is to link the three components: Statistics - industry - computers. Different areas of industrial statistics are presented by a number of excellent contributions. The following topics are covered: Quality control, engineering and monitoring; reliability and failure time analysis, experimental design; repeated measurements - multiple inference; pharma - statistics; computing, imaging and perception. This book concentrates on the interface between statistical needs in industry and statistical methods developed by statisticians and engineers.

Zielgruppe

Research

Autoren/Hrsg.

Kitsos, Christos P.

Edler, Lutz

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Kosmetische Technologie
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Pharmazie
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik

Inhaltsverzeichnis

I. Quality Control, Engineering and Monitoring.- Quality Engineering Using Robust Design and Analysis.- The Calibration Problem in Industry.- Case Study of Applying Statistical Techniques for the Quality Assurance in a Paint Industry.- Taking Multivariate Statistics out into Industry — Multivariate Statistical Progress Control and Process Performance Monitoring.- Robust Estimation of Variance Components with High Breakdown Point in the 1-Way Random Effect Model.- Sources of Inaccuracy in the Mean and Variance Models for Quality Improvement Problems.- II. Reliability and Failure Time Analysis.- Accelerated Life Test with Some Parameter Change in Life Stress Relation.- Accurate Inferences for the Reliability Function Considering Accelerated Life Tests.- Prediction of Failures that Have Never Occured — Exponential Case.- Algorithm of Confidence Limits Calculation for the Probability of the Value 1 of a Monotone Boolean Function of Random Variables.- Developing a Graphical Interface for Pre-Posterior Bayesian Analysis.- III. Experimental Design.- Nonlinear-Optimal-Sequential Experiment Designs and Applications.- Robust Inference and Experimental Design for Multi-Factor Models.- Construction of Some New Orthogonal Main-Effect Designs.- Extended V-robustness for Two-level Orthogonal Resolution V Designs.- Computational Algebraic Geometry in Industrial Experimental Design.- IV. Pharmaceutical Statistics.- New Statistical Methods for Analyzing Mutagenicity Assays Real Data Problems in Biopharmaceutical Drug Development:.- Application of Statistical Selection Procedures in Biotechnology.- Modeling and Computation in Pharmaceutical Statistics when Analyzing Drug Safety.- Isotonic Inference with Particular Interest in Application to Clinical Trials.- Tests for Linearity andTests for Zero Slope in Crossover Studies.- V. Repeated Measurements — Multiple Inference.- A Nonparametric Combination Method for Dependent Permutation Tests with Application to Some Problems with Repeated Measures.- Adaptive Tests for Trend.- VI. Computing, Imaging and Prediction.- Convergence Rates of Simulated Annealing-Type of Recursive Algorithms.- Spatial Statistics in the Material Research.- Exact Solutions to the Problem of Predicting a Vast Class of Weakly Stationary, Linearly Singular, Discrete Parameter Stochastic Processes.