Multivariate Data Analysis

Author: Joseph F. Hair (Jr),William C. Black,Barry J. Babin,Rolph E. Anderson

Publisher: N.A

ISBN: 9781292021904

Category: Multivariate analysis

Page: 752

View: 6959

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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.
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Multivariate Data Analysis - in Practice

An Introduction to Multivariate Data Analysis and Experimental Design

Author: Kim H. Esbensen,Dominique Guyot,Frank Westad,Lars P. Houmoller

Publisher: Multivariate Data Analysis

ISBN: 9788299333030

Category: Experimental design

Page: 598

View: 3291

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"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.
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Exploratory and Multivariate Data Analysis

Author: Michel Jambu

Publisher: Elsevier

ISBN: 0080923674

Category: Mathematics

Page: 432

View: 7316

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With a useful index of notations at the beginning, this book explains and illustrates the theory and application of data analysis methods from univariate to multidimensional and how to learn and use them efficiently. This book is well illustrated and is a useful and well-documented review of the most important data analysis techniques. Key Features * Describes, in detail, exploratory data analysis techniques from the univariate to the multivariate ones * Features a complete description of correspondence analysis and factor analysis techniques as multidimensional statistical data analysis techniques, illustrated with concrete and understandable examples * Includes a modern and up-to-date description of clustering algorithms with many properties which gives a new role of clustering in data analysis techniques
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Making Sense of Multivariate Data Analysis

An Intuitive Approach

Author: John Spicer

Publisher: SAGE

ISBN: 9781412904018

Category: Mathematics

Page: 233

View: 5900

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′This book is a helpful guide to reading and understanding multivariate data analysis results in social and psychological research′ _C. Y. Joanne Peng, Indiana University at Bloomington ′This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses′ _Jenn-Yun Tein, Arizona State University
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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, 2001

Author: Hans-Hermann Bock,Marcello Chiodi,Antonio Mineo

Publisher: Springer Science & Business Media

ISBN: 3642171117

Category: Mathematics

Page: 281

View: 8733

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The book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology.
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The Analysis and Interpretation of Multivariate Data for Social Scientists

Author: J.I. Galbraith,Irini Moustaki,David J. Bartholomew,Fiona Steele

Publisher: CRC Press

ISBN: 9781584882954

Category: Mathematics

Page: 280

View: 9726

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Multivariate analysis is an important tool for social researchers, but the subject is broad and can be quite technical for those with limited mathematical and statistical backgrounds. To effectively acquire the tools and techniques they need to interpret multivariate data, social science students need clear explanations, a minimum of mathematical detail, and a wide range of exercises and worked examples. Classroom tested for more than 10 years, The Analysis and Interpretation of Multivariate Data for Social Scientists describes and illustrates methods of multivariate data analysis important to the social sciences. The authors focus on interpreting the pattern of relationships among many variables rather than establishing causal linkages, and rely heavily on numerical examples, visualization, and on verbal , rather than mathematical exposition. They present methods for categorical variables alongside the more familiar method for continuous variables and place particular emphasis on latent variable techniques. Ideal for introductory, senior undergraduate and graduate-level courses in multivariate analysis for social science students, this book combines depth of understanding and insight with the practical details of how to carry out and interpret multivariate analyses on real data. It gives them a solid understanding of the most commonly used multivariate methods and the knowledge and tools to implement them. Datasets, the SPSS syntax and code used in the examples, and software for performing latent variable modelling are available at http://www.mlwin.com/team/aimdss.html>
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Applied Multivariate Statistical Analysis

Author: Wolfgang Karl Härdle,Léopold Simar

Publisher: Springer

ISBN: 3662451719

Category: Business & Economics

Page: 580

View: 5272

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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.
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Applied Multivariate Statistical Analysis

Author: Wolfgang Härdle,Léopold Simar

Publisher: Springer Science & Business Media

ISBN: 3540722432

Category: Business & Economics

Page: 458

View: 6612

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With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility as it presents tools and concepts in a way that is understandable for non-mathematicians.
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Introduction to Multivariate Statistical Analysis in Chemometrics

Author: Kurt Varmuza,Peter Filzmoser

Publisher: CRC Press

ISBN: 9781420059496

Category: Science

Page: 336

View: 5868

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Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as principal component analysis, regression analysis, classification methods, and clustering. Written by a chemometrician and a statistician, the book reflects the practical approach of chemometrics and the more formally oriented one of statistics. To enable a better understanding of the statistical methods, the authors apply them to real data examples from chemistry. They also examine results of the different methods, comparing traditional approaches with their robust counterparts. In addition, the authors use the freely available R package to implement methods, encouraging readers to go through the examples and adapt the procedures to their own problems. Focusing on the practicality of the methods and the validity of the results, this book offers concise mathematical descriptions of many multivariate methods and employs graphical schemes to visualize key concepts. It effectively imparts a basic understanding of how to apply statistical methods to multivariate scientific data.
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Essentials of Multivariate Data Analysis

Author: Neil H. Spencer

Publisher: CRC Press

ISBN: 1466584785

Category: Mathematics

Page: 186

View: 6454

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Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel® can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book’s CRC Press web page. Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab®, R, SAS, SPSS, and Stata.
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