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Multivariate Humanities: Quantitative Methods in the Humanities and Social Sciences

Autor Pieter M. Kroonenberg
en Limba Engleză Paperback – 30 iun 2022
This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of datasets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.
Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.
The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary. Datasets in SPSS are included online.
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Specificații

ISBN-13: 9783030691523
ISBN-10: 3030691527
Pagini: 436
Ilustrații: XXI, 436 p. 148 illus., 123 illus. in color.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.64 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Quantitative Methods in the Humanities and Social Sciences

Locul publicării:Cham, Switzerland

Cuprins

1. Introduction: Multivariate studies in the Humanities.- 2. Data inspection: The data are in. Now what?- 3. Statistical framework.- 4. Statistical framework extended.- 5. Similarity data: Bible translations (coauthor: Zachary Bleemer).- 6. Stylometry: Authorship of the Pauline Epistles.- 7. Economic history: Agriculture development on Java.- 8. Seriation: Graves in the Münsingen-Rain burial site.- 9. Complex response data: Evaluating Marian art (coauthor: Donald Polzella).- 10. Rating scales: Craquelure and pictorial stylometry (coauthor: Spike Bucklow).- 11. Pictorial similarity: Rock art images across the world.- 12 Questionnaires: Public views on deaccessioning (coauthor: Marilena Vecco).- 13. Sylometry: The Royal Book of Oz: Baum or Thompson?- 14. Linguistics: Accentual prose rhythm in medieval Latin.- 15. Linguistics: Chronology of Plato's works.- 16. Binary judgments: Reading preferences.- 17. Music appreciation: The Chopin Preludes (coauthor: Takashi Murakami).- 18. Musical stylometry: Characterisation of music (coauthor: Dorien Herremans).- 19. Final musings.

Notă biografică

Pieter Kroonenberg, PhD, is Emeritus Professor of Multivariate Analysis, in particular of three-mode data, at Leiden University in The Netherlands. He has over forty years of academic, teaching and consulting experience, and has published two books as well as over 150 technical and applied papers in a wide range of disciplines.

Textul de pe ultima copertă

This case study-based textbook in multivariate analysis for advanced students in the humanities emphasizes descriptive, exploratory analyses of various types of data sets from a wide range of sub-disciplines, promoting the use of multivariate analysis and illustrating its wide applicability. Fields featured include, but are not limited to, historical agriculture, arts (music and painting), theology, and stylometrics (authorship issues). Most analyses are based on existing data, earlier analysed in published peer-reviewed papers.
Four preliminary methodological and statistical chapters provide general technical background to the case studies. The multivariate statistical methods presented and illustrated include data inspection, several varieties of principal component analysis, correspondence analysis, multidimensional scaling, cluster analysis, regression analysis, discriminant analysis, and three-mode analysis.
The bulk of the text is taken up by 14 case studies that lean heavily on graphical representations of statistical information such as biplots, using descriptive statistical techniques to support substantive conclusions. Each study features a description of the substantive background to the data, followed by discussion of appropriate multivariate techniques, and detailed results interpreted through graphical illustrations. Each study is concluded with a conceptual summary.

Caracteristici

Includes chapter-level datasets in SPSS Features case studies, examples, and problems from a large variety of sub-disciplines Emphasizes data visualization with graphical illustrations of results Includes supplementary material: sn.pub/extras