Multiple Correspondence Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Correspondence Analysis write by Brigitte Le Roux. This book was released on 2010. Multiple Correspondence Analysis available in PDF, EPUB and Kindle. "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.
Multiple Correspondence Analysis and Related Methods
Multiple Correspondence Analysis and Related Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Correspondence Analysis and Related Methods write by Michael Greenacre. This book was released on 2006-06-23. Multiple Correspondence Analysis and Related Methods available in PDF, EPUB and Kindle. 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
Multiple Correspondence Analysis for the Social Sciences
Multiple Correspondence Analysis for the Social Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple Correspondence Analysis for the Social Sciences write by Johs. Hjellbrekke. This book was released on 2018-06-18. Multiple Correspondence Analysis for the Social Sciences available in PDF, EPUB and Kindle. 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.
Practical Guide To Principal Component Methods in R
Practical Guide To Principal Component Methods in R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Practical Guide To Principal Component Methods in R write by Alboukadel KASSAMBARA. This book was released on 2017-08-23. Practical Guide To Principal Component Methods in R available in PDF, EPUB and Kindle. 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.
Visualization and Verbalization of Data
Visualization and Verbalization of Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Visualization and Verbalization of Data write by Jorg Blasius. This book was released on 2014-04-10. Visualization and Verbalization of Data available in PDF, EPUB and Kindle. 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
