Multivariate Data Analysis
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Multivariate Data Analysis
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Author : Joseph F. Hair (Jr.)
language : en
Publisher: Pearson
Release Date : 2010
Multivariate Data Analysis written by Joseph F. Hair (Jr.) and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Business & Economics categories.
Offering an applications-oriented approach which focuses on the use of each technique rather than its mathematical derivation, this textbook introduces a six-step framework for organising and discussing multivariate data analysis techniques.
Multivariate Data Analysis
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Author : JOSEPH. HAIR
language : en
Publisher:
Release Date : 2018-05-22
Multivariate Data Analysis written by JOSEPH. HAIR and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-22 with categories.
Multivariate Data Analysis
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Author : Kim H. Esbensen
language : en
Publisher: Multivariate Data Analysis
Release Date : 2002
Multivariate Data Analysis written by Kim H. Esbensen and has been published by Multivariate Data Analysis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Experimental design categories.
"Multivariate Data Analysis - in practice adopts a practical, non-mathematical approach to multivariate data analysis. The book's principal objective is to provide a conceptual framework for multivariate data analysis techniques, enabling the reader to apply these in his or her own field. Features: Focuses on the practical application of multivariate techniques such as PCA, PCR and PLS and experimental design. Non-mathematical approach - ideal for analysts with little or no background in statistics. Step by step introduction of new concepts and techniques promotes ease of learning. Theory supported by hands-on exercises based on real-world data. A full training copy of The Unscrambler (for Windows 95, Windows NT 3.51 or later versions) including data sets for the exercises is available. Tutorial exercises based on data from real-world applications are used throughout the book to illustrate the use of the techniques introduced, providing the reader with a working knowledge of modern multivariate data analysis and experimental design. All exercises use The Unscrambler, a de facto industry standard for multivariate data analysis software packages. Multivariate Data Analysis in Practice is an excellent self-study text for scientists, chemists and engineers from all disciplines (non-statisticians) wishing to exploit the power of practical multivariate methods. It is very suitable for teaching purposes at the introductory level, and it can always be supplemented with higher level theoretical literature."Résumé de l'éditeur.
Multivariate Data Analysis
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Author : Joseph F. Hair (Jr)
language : en
Publisher:
Release Date : 2013
Multivariate Data Analysis written by Joseph F. Hair (Jr) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Multivariate analysis categories.
Offering an applications-oriented approach which focuses on the use of each technique rather than its mathematical derivation, this textbook introduces a six-step framework for organising and discussing multivariate data analysis techniques.
Multivariate Data Analysis With Readings
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Author : Joseph F. Hair
language : en
Publisher: Macmillan College
Release Date : 1995
Multivariate Data Analysis With Readings written by Joseph F. Hair and has been published by Macmillan College this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business & Economics categories.
Examining your data. Multiple regression analysis. Multiple discriminat analysis. Multivariate analysis of variance. Canonical correlation analysis. Factor analysis. Cluster analysis. Multidimensional scaling. Conjoint analysis. Structural equation modeling.
Multi And Megavariate Data Analysis Basic Principles And Applications
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Author : L. Eriksson
language : en
Publisher: Umetrics Academy
Release Date : 2013-07-01
Multi And Megavariate Data Analysis Basic Principles And Applications written by L. Eriksson and has been published by Umetrics Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-01 with Mathematics categories.
To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.
Multivariate Data Analysis
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Author : William W. Cooley
language : en
Publisher:
Release Date : 1985
Multivariate Data Analysis written by William W. Cooley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.
Applied Multivariate Statistical Analysis
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2015-02-26
Applied Multivariate Statistical Analysis written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with Business & Economics categories.
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields. All of the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features: A new chapter on Variable Selection (Lasso, SCAD and Elastic Net) All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de. The practical exercises include solutions that can be found in Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.
Multivariate Data Analysis Pearson New International Edition Pdf Ebook
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Author : Joseph F. Hair
language : en
Publisher: Pearson Higher Ed
Release Date : 2013-08-27
Multivariate Data Analysis Pearson New International Edition Pdf Ebook written by Joseph F. Hair and has been published by Pearson Higher Ed this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-27 with Business & Economics categories.
For graduate and upper-level undergraduate marketing research courses. For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. The authors provide 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 7th Edition, the organisation 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. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
Applied Multivariate Data Analysis
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Author : Brian S. Everitt
language : en
Publisher: Wiley
Release Date : 2010-06-28
Applied Multivariate Data Analysis written by Brian S. Everitt and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-28 with Mathematics categories.
Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major chapter revisions as well as new sections on neural networks and random effects models for longitudinal data. Maintaining the easy-going style of the first edition, the authors provide clear explanations of each technique, as well as supporting figures and examples, and minimal technical jargon. With extensive exercises following every chapter, 'Applied Multivariate Data Analysis' is a valuable resource for students on applied statistics courses and applied researchers in many disciplines.