Multiple Correspondence Analysis And Related Methods
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Multiple Correspondence Analysis And Related Methods
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Author : Michael Greenacre
language : en
Publisher: CRC Press
Release Date : 2006-06-23
Multiple Correspondence Analysis And Related Methods written by Michael Greenacre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-23 with Mathematics categories.
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su
Visualization And Verbalization Of Data
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Author : Jorg Blasius
language : en
Publisher: CRC Press
Release Date : 2014-04-10
Visualization And Verbalization Of Data written by Jorg Blasius and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-10 with Mathematics categories.
Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in the verbalization of the structures in data. Renowned researchers in the field trace the history of these techniques and cover their current applications.The first part of the book explains
Multiple Correspondence Analysis
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Author : Brigitte Le Roux
language : en
Publisher: SAGE
Release Date : 2010
Multiple Correspondence Analysis written by Brigitte Le Roux and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Social Science categories.
Requiring no prior knowledge of correspondence analysis, this text provides a nontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte LeRoux and Henry Rouanet, present thematerial in a practical manner, keeping the needs of researchers foremost in mind. Key Features Readers learn how to construct geometric spaces from relevant data, formulate questions of interest, and link statistical interpretation to geometric representations. They also learn how to perform structured data analysis and to draw inferential conclusions from MCA. The text uses real examples to help explain concepts. The authors stress the distinctive capacity of MCA to handle full-scale research studies. This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as for individual researchers. Learn more about The Little Green Book - QASS Series! Click Here
Multiple Correspondence Analysis For The Social Sciences
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Author : Johs. Hjellbrekke
language : en
Publisher: Routledge
Release Date : 2018-06-18
Multiple Correspondence Analysis For The Social Sciences written by Johs. Hjellbrekke and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-18 with Social Science categories.
Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930–2002). This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own.
Multiple Correspondence Analysis
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Author : Brigitte Le Roux
language : en
Publisher:
Release Date : 2010
Multiple Correspondence Analysis written by Brigitte Le Roux and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Correspondence analysis (Statistics) categories.
This work provides a nontechnical introduction to multiple correspondence analysis as a method in its own right. The presentation is practically oriented and with the needs of research in mind: gathering relevant data, formulating questions of interest, and linking statistical interpretation to geometric representations.
Correspondence Analysis In Practice Third Edition
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Author : Michael Greenacre
language : en
Publisher: CRC Press
Release Date : 2017-01-20
Correspondence Analysis In Practice Third Edition written by Michael Greenacre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-20 with Mathematics categories.
Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA and joint CA, translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social, environmental and health sciences, as well as marketing, economics, linguistics, archaeology, and more. Michael Greenacre is Professor of Statistics at the Universitat Pompeu Fabra, Barcelona, Spain, where he teaches a course, amongst others, on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters, mostly on correspondence analysis, the latest being Visualization and Verbalization of Data in 2015. He has given short courses in fifteen countries to environmental scientists, sociologists, data scientists and marketing professionals, and has specialized in statistics in ecology and social science.
Biplots In Practice
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Author : Michael J. Greenacre
language : en
Publisher: Fundacion BBVA
Release Date : 2010
Biplots In Practice written by Michael J. Greenacre and has been published by Fundacion BBVA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Fishes categories.
Este libro explica las aplicaciones específicas y las interpretaciones del biplot en muchas áreas del análisis multivariante. regresión, modelos lineales generalizados, análisis de componentes principales, análisis de correspondencias y análisis discriminante.
Exploratory Multivariate Analysis By Example Using R
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Author : Francois Husson
language : en
Publisher: CRC Press
Release Date : 2017-04-25
Exploratory Multivariate Analysis By Example Using R written by Francois Husson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Mathematics categories.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a
Practical Guide To Principal Component Methods In R
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Author : Alboukadel KASSAMBARA
language : en
Publisher: STHDA
Release Date : 2017-08-23
Practical Guide To Principal Component Methods In R written by Alboukadel KASSAMBARA and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-23 with categories.
Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.
Multiple Correspondence Analysis
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Author : Brigitte Le Roux
language : en
Publisher: SAGE
Release Date : 2010
Multiple Correspondence Analysis written by Brigitte Le Roux and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
"Requiring no prior knowledge of correspondence analysis, this text provides anontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte Le Roux and Henry Rouanet, present the material in a practical manner, keeping the needs of researchers foremost in mind." "This supplementary text isappropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as forindividual researchers." --Book Jacket.