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Author: Francis Gendre
Publisher: Librairie Droz
ISBN:
Category : Matrices
Languages : fr
Pages : 422
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Book Description
Author: Francis Gendre
Publisher: Librairie Droz
ISBN:
Category : Matrices
Languages : fr
Pages : 422
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Book Description
Author: Jérôme Pagès
Publisher: EDP Sciences
ISBN: 2759810852
Category : Mathematics
Languages : fr
Pages : 269
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Book Description
L’analyse factorielle multiple (AFM ) est la méthode de référence pour analyser des tableaux de données dans lesquels un ensemble d’individus est décrit par plusieurs groupes de variables, ces dernières pouvant être quantitatives et/ou qualitatives. Ce type de tableau multiple se rencontre dans de nombreux domaines comme les enquêtes (les questionnaires comportent toujours plusieurs thèmes : des opinions, des comportements, etc.) ou les sciences expérimentales (dans l’industrie agro-alimentaire, par exemple, on caractérise les produits à la fois par des données physico-chimiques et des données issues de dégustations). Ce livre est destiné aux utilisateurs confrontés à des tableaux multiples. Une large place est accordée aux applications et à la mise en oeuvre via R. L’objectif est de rendre l’utilisateur autonome dans l’application de l’AFM sur ses données. Dans cet esprit, ce livre : – introduit une à une les principales caractéristiques de la méthode intuitivement à partir d’exemples ; – donne les éléments théoriques nécessaires pour une compréhension en profondeur avec un recours au raisonnement géométrique systématique ; – illustre les résultats à partir des exemples introductifs ; – détaille la marche à suivre pour appliquer l’AFM avec le package FactoMineR ou via des codes R. Ces codes sont disponibles sur le site du LMA 2 (Agrocampus). Cet exposé est complété par une présentation des méthodes classiques, ACP et ACM , elle aussi fondée sur des exemples. L’ensemble constitue l’état de l’art aujourd’hui en analyse factorielle. Jérôme Pagès est professeur de statistique à Agrocampus (Rennes) où il dirige le laboratoire de mathématiques appliquées (LMA2).
Author: Jean Stafford
Publisher: PUQ
ISBN: 9782760518735
Category : Mathematics
Languages : fr
Pages : 260
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Book Description
Les auteurs proposent une approche pratique et empirique qui allie l'analyse statistique à l'utilisation d'un logiciel facile d'accès : SPSS. En décrivant les diverses méthodes de l'analyse multivariée, ils présentent les interrelations entre plusieurs variables d'une base de données et en généralisent les conclusions par inférence statistique du traitement informatique des données jusqu'à l'interprétation des résultats.
Author: L. Eriksson
Publisher: Umetrics Academy
ISBN: 9197373052
Category : Mathematics
Languages : en
Pages : 509
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Book Description
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.
Author: David G. Kleinbaum
Publisher: PWS Publishing Company
ISBN:
Category : Mathematics
Languages : en
Pages : 584
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Book Description
Author: Bruce L. Brown
Publisher: John Wiley & Sons
ISBN: 1118131614
Category : Mathematics
Languages : en
Pages : 404
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Book Description
An insightful guide to understanding and visualizing multivariate statistics using SAS®, STATA®, and SPSS® Multivariate Analysis for the Biobehavioral and Social Sciences: A Graphical Approach outlines the essential multivariate methods for understanding data in the social and biobehavioral sciences. Using real-world data and the latest software applications, the book addresses the topic in a comprehensible and hands-on manner, making complex mathematical concepts accessible to readers. The authors promote the importance of clear, well-designed graphics in the scientific process, with visual representations accompanying the presented classical multivariate statistical methods . The book begins with a preparatory review of univariate statistical methods recast in matrix notation, followed by an accessible introduction to matrix algebra. Subsequent chapters explore fundamental multivariate methods and related key concepts, including: Factor analysis and related methods Multivariate graphics Canonical correlation Hotelling's T-squared Multivariate analysis of variance (MANOVA) Multiple regression and the general linear model (GLM) Each topic is introduced with a research-publication case study that demonstrates its real-world value. Next, the question "how do you do that?" is addressed with a complete, yet simplified, demonstration of the mathematics and concepts of the method. Finally, the authors show how the analysis of the data is performed using Stata®, SAS®, and SPSS®. The discussed approaches are also applicable to a wide variety of modern extensions of multivariate methods as well as modern univariate regression methods. Chapters conclude with conceptual questions about the meaning of each method; computational questions that test the reader's ability to carry out the procedures on simple datasets; and data analysis questions for the use of the discussed software packages. Multivariate Analysis for the Biobehavioral and Social Sciences is an excellent book for behavioral, health, and social science courses on multivariate statistics at the graduate level. The book also serves as a valuable reference for professionals and researchers in the social, behavioral, and health sciences who would like to learn more about multivariate analysis and its relevant applications.
Author: Karen A. Randolph
Publisher: Oxford University Press, USA
ISBN: 0199764042
Category : Mathematics
Languages : en
Pages : 224
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Book Description
This pocket guide introduces readers to linear regression analysis, analysis of variance and covariance, and path analysis with an emphasis on the basic statistics. It prepares doctoral students and early career social work researchers with limited statistics exposure in the use of multivariate methods by providing an easy-to-understand presentation.
Author: George A. Marcoulides
Publisher: Psychology Press
ISBN: 1317778545
Category : Psychology
Languages : en
Pages : 338
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Book Description
Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is pointing out the analogy between a common univariate statistical technique and the corresponding multivariate method. Many computer examples--drawing on SAS software --are used as demonstrations. Throughout the book, the computer is used as an adjunct to the presentation of a multivariate statistical method in an empirically oriented approach. Basically, the model adopted in this book is to first present the theory of a multivariate statistical method along with the basic mathematical computations necessary for the analysis of data. Subsequently, a real world problem is discussed and an example data set is provided for analysis. Throughout the presentation and discussion of a method, many references are made to the computer, output are explained, and exercises and examples with real data are included.
Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
ISBN: 9783540030799
Category : Business & Economics
Languages : en
Pages : 502
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Book Description
These are the exciting memoirs of an articulate black lady, who survived the destitution of her childhood by scavenging in the Mobile, Alabama, city dump. She lived in the segregated South during the era of Civil Rights demonstrations. As a mother of six, she overcame the shock of discovering she was one of several wives with whom her itinerant preacher husband claimed conjugal privileges. She became an artist's model in Boston, where she experienced racist terror and love of a white man. This is a beautiful, upbeat book of love, happiness and the survival of the spirit.
Author: Régis Gras
Publisher: CRC Press
ISBN: 100381302X
Category : Mathematics
Languages : en
Pages : 259
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Book Description
This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA), created by Régis Gras in the 1980s to study, in a new way, the behavioural responses of French pupils to mathematics tests. Using a multidimensional, non-symmetrical data analysis method, SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA, through its various extensions, is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules, from a set of variables. It is based on the unlikeliness of the existence of these relationships, i.e. on the relative weakness of their counter-examples compared to what chance alone would produce. It establishes a dual topological relationship between the set of subjects and the set of variables. Many applications of this approach, driving forces or crucibles for the development of SIA, have concerned and still concern various fields such as didactics, evaluation and assessment, psychology, sociology, medicine, biology, economics, art history, and others. Key Features: Presents the foundations and representations of SIA. Provides extensions of variable sets and subjects. Includes a bonus exercise.
