LEADER 03898oam 2200637I 450 001 9910799990403321 005 20200812213934.0 010 $a0-429-16798-9 010 $a1-4665-8981-7 024 7 $a10.1201/b16741 035 $a(CKB)2550000001254756 035 $a(EBL)1414098 035 $a(SSID)ssj0001133154 035 $a(PQKBManifestationID)11639791 035 $a(PQKBTitleCode)TC0001133154 035 $a(PQKBWorkID)11157227 035 $a(PQKB)11223342 035 $a(OCoLC)875095865 035 $a(MiAaPQ)EBC1414098 035 $a(EXLCZ)992550000001254756 100 $a20180331h20142014 uy 0 101 0 $aeng 135 $aur|n||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aVisualization and verbalization of data /$fedited by Jorg Blasius, University of Bonn, Germany, Michael Greenacre, Universitat Pompeu Fabra, Barcelona, Spain 210 1$aBoca Raton :$cCRC Press,$d[2014] 210 4$dİ2014 215 $a1 online resource (382 p.) 225 1 $aChapman and Hall/CRC Computer Science and Data Analysis 300 $aDescription based upon print version of record. 311 $a1-4665-8980-9 311 $a1-306-56796-3 320 $aIncludes bibliographical references. 327 $aFront Cover; Contents; Foreword; Preface; Editors; Contributors; Prologue: Let the Data Speak!; Chapter 1: Some Prehistory of CARME: Visual Language and Visual Thinking; Chapter 2: Some History of Algebraic Canonical Forms and Data Analysis; Chapter 3: Historical Elements of Correspondence Analysis and Multiple Correspondence Analysis; Chapter 4: History of Nonlinear Principal Component Analysis; Chapter 5: History of Canonical Correspondence Analysis; Chapter 6: History of Multiway Component Analysis and Three-Way Correspondence Analysis 327 $aChapter 7: Past, Present, and Future of Multidimensional ScalingChapter 8: History of Cluster Analysis; Chapter 9: Simple Correspondence Analysis; Chapter 10: Distributional Equivalence and Linguistics; Chapter 11: Multiple Correspondence Analysis; Chapter 12: Structured Data Analysis; Chapter 13: Empirical Construction of Bourdieu's Social Space; Chapter 14: Multiple Factor Analysis:General Presentation and Comparison with STATIS; Chapter 15: Data Doubling and Fuzzy Coding; Chapter 16: Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data 327 $aChapter 17: Group Average Linkage Compared to Ward's Method in Hierarchical ClusteringChapter 18: Analysing a Pair of Tables: Coinertia Analysis and Duality Diagrams; References; Back Cover 330 $aThis volume presents an overview of the state of the art in data visualization, encompassing correspondence analysis, nonlinear principal component analysis, cluster analysis, multidimensional scaling, and much more. It covers the historical development of each topic along with modern techniques and future research directions. To illustrate the methods, the book incorporates many real data examples and software implementations. Each chapter is written by leading researchers in the field and thoroughly edited to ensure coherence and consistency--$cProvided by publisher. 410 0$aSeries in computer science and data analysis. 606 $aInformation visualization 606 $aCorrespondence analysis (Statistics) 606 $aMultiple comparisons (Statistics) 615 0$aInformation visualization. 615 0$aCorrespondence analysis (Statistics) 615 0$aMultiple comparisons (Statistics) 676 $a001.4/226 686 $aMAT029000$2bisacsh 702 $aBlasius$b Jorg$f1957- 702 $aGreenacre$b Michael J. 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910799990403321 996 $aVisualization and verbalization of data$91498352 997 $aUNINA