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Advances in Multivariate Data Analysis

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  • 40 Currently reading

Published by Springer .
Written in English

Subjects:

  • Probability & statistics,
  • Trees & Forests - General,
  • Mathematics,
  • Business / Economics / Finance,
  • Statistics,
  • Science/Mathematics,
  • Multivariate analysis,
  • Biostatistics,
  • Computer Vision,
  • Business & Economics / Statistics,
  • Computers-Computer Vision,
  • Medical-Biostatistics,
  • Probability & Statistics - General,
  • Congresses,
  • Business & Economics

Book details:

Edition Notes

ContributionsHans-Hermann Bock (Editor), Marcello Chiodi (Editor), Antonio Mineo (Editor)
The Physical Object
FormatPaperback
Number of Pages281
ID Numbers
Open LibraryOL9054516M
ISBN 103540208895
ISBN 109783540208891

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Advances in Multivariate Data Analysis Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5–6, Editors: Bock, Hans-Hermann, Chiodi, Marcello, Mineo, Antonio (Eds.) Free Preview. Multivariate Data Analysis is an applications-oriented introduction to multivariate analysis for the non-statistician. The eighth edition incorporates pivotal advances in technology that will assist students in gaining a firm understanding of statistical and managerial principles so as to develop a "comfort zone" not only for the statistical, but also the practical issues involved. KEY BENEFIT: For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. Hair, et. al 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. Advances in Multivariate Statistical Analysis Pillai Memorial Volume. Editors (view affiliations) A. K. Gupta; Book. Citations; k Downloads; Part of the Theory and Decision Library book series (TDLB, volume 5) Log in to check access. Buy eBook. USD Some Simple Optimal Tests in Multivariate Analysis. Govind S. Mudholkar, Perla.

"Multivariate Data Analysis is an applications-oriented introduction to multivariate analysis for the non-statistician. The seventh edition incorporates pivotal advances in technology that will assist students in gaining a firm understanding of statistical and managerial principles so as to develop a "comfort zone" not only for the statistical, but also the practical issues involved."--Jacket.   KEY BENEFIT: For over 30 years, this text has provided students with the information they need to understand and apply multivariate data , et. al 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 Reviews: Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. for the first time in a book on multivariate analysis. KEY BENEFIT: For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. Hair, et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician.

Comprehensive Chemometrics, Second Edition features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods.   For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the s: Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory. The multi-dimensional character of the data requires the application of advanced multivariate data analysis (MVDA) tools. An overview of both linear and non-linear MVDA tools most frequently used in bioprocess data analysis is presented.