Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods

Die Datenanalyse mit mehreren Variablen gehört zum Alltag der Chemometrie. Die Autoren sind ausgezeichnete Spezialisten auf dem Gebiet der multivariaten Analyse. Sie geben hier in saloppem Stil und aufgelockert durch zahlreiche witzige Cartoons eine verständliche Einführung in dieses Thema. Erläutert werden eine Reihe von Anwendungen bei der Qualitätskontrolle, insbesondere in der Nahrungsmittelindustrie. Mit zahlreichen Kontrollfragen und Übungsaufgaben!

​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.

Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods

Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.

Provides a theoretical foundation as well as practical tools for the analysis of multivariate data, using case studies and MINITAB computer macros to illustrate basic and advanced quality control methods. This work offers an approach to quality control that relies on statistical tolerance regions, and discusses computer graphic analysis highlightin

This volume contains a collection of research articles on multivariate statistical methods, encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. It serves as a tribute to Professor S N Roy, an eminent statistician who has made seminal contributions to the area of multivariate statistical methods, on his birth centenary. In the area of emerging applications, the topics include bioinformatics, categorical data and clinical trials, econometrics, longitudinal data analysis, microarray data analysis, sample surveys, statistical process control, etc.Researchers, professionals and advanced graduates will find the book an essential resource for modern developments in theory as well as for innovative and emerging important applications in the area of multivariate statistical methods.