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"Proses pengendalian mutu statistik berperan penting dalam pemantauan proses produksi. Pemantauan proses yang melibatkan beberapa peubah secara bersama-sama disebut dengan pengendalian mutu statistik multivariat. Pemantauan proses dapat dilakukan dengan menggunakan bagan kendali multivariate. Tujuan dari bagan kendali multivariat adalah untuk mengetahui apakah proses yang dilakukan terkendali atau tidak dan salah satu bagan yang sering digunakan dalam pengendalian mutu statistik multivariat adalah bagan kendali Hotelling T 2 . Pada skripsi ini akan membahas bagan kendali Hotelling T 2 yang digunakan untuk memantau proses pada fase I dan fase II. Namun bagan kendali Hotelling T 2 tidak dapat mengidentifikasi penyebab masalah jika pada bagan terdapat outlier. Oleh karena itu digunakan dekomposisi dari T 2 ( dekomposisi MYT ) untuk mengidentifikasi peubah mana yang secara signifikan menyebabkan proses tidak terkendali. "

"Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying data structure of these and many other quantitative studies of applied sciences is multivariate. Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics. All chapters have exercises that highlight applications in different fields. The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features. A new Chapter on Regression Models has been added. All numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets."

"For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. This text provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques."